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Successful Scien+fic Wri+ng Eugene Elbert, MS (Johns Hopkins
University, U.S.) Special thanks to : Paul Siegel MD, MPH
9-‐10 August 2012
Biological Threat Reduc+on Program of the
Defense Threat Reduc+on Agency (DTRA)
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Biological Threat Reduc+on Program
• Consolidate especially dangerous pathogens (EDPs) into one or two safe, secure central reference laboratories or repositories
• Build and sustain long-‐term partnerships through interna+onal scien+fic engagement and coopera+on
• Improve capacity to detect, diagnose and report outbreaks and poten+al pandemics by providing training to personnel of the appropriate facili+es
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Biological Threat Reduc+on Program (BTRP)
• EDPs for human and animal health include: o Avian and pandemic influenza (influenza viruses) o Crimean-‐Congo Hemorrhagic Fever (CCHF virus) o Anthrax (Bacillus anthracis) o Brucella (Brucella species) o Tularemia (Francisella tularensis) o Botulism (Clostridium botulinum) o Tick Borne Encephali+s (TBE virus) o Plague (Yersinia pes6s) o Foot and Mouth Disease (FMD) o Glanders o Newcastle Disease Virus o Rinderpest o Pox viruses (goat and sheep pox) o Swine fevers (African and Classical Swine Fever)
• Although the BTRP-‐provided training focus on these pathogens, the knowledge and skills learned and prac+ced are applicable to a broad range of other infec+ous diseases and public and animal health concerns
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BTRP-‐Provided Training
Courses include: • Disease recogni+on; • Laboratory equipment use and maintenance; • Biosafety and security; • Laboratory safety; • Laboratory quality systems; • Respiratory protec+on program; • Purchasing and inventory control; • Introduc+on to microbiology; • Introduc+on to molecular biology; • Introduc+on to immunology/serology; • Diagnos+c assays for specific EDPs; • Laboratory management; • Sample collec+on and processing; • Basics of epidemiology; and others
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Conceptual design of approved TIPME Training Facility
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BTRP Summary
• Enhancement of exis+ng surveillance capacity through expansion of generic skills
• Development of capacity for rapid detec+on (PCR and ELISA), which contributes to public health
• Improved biosafety and biosecurity for laboratory personnel
• BTRP-‐provided training complements the Ministry training requirements for specialists
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Successful Scien+fic Wri+ng
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Introduc+on
Objec+ves of the workshop: • To introduce basic concepts of scien+fic approach • To detail the structure and format of scien+fic papers. • To compare examples of different research designs. • To examine components of a scien+fic paper. • To cri+cally examine published examples of scien+fic wri+ng.
• To apply new wri+ng skills to draging an abstract. • To learn about the submission process for publica+ons, funding proposals, and presenta+ons
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Why do we publish?
• Presen+ng research • Reaching global scien+fic community • Advancing science • Educa+on • Funding and credibility
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Repor+ng Scien+fic Research
• Hypothesis or research ques+on • Planned research • Ethics
– Plagiarism – Misuse of data and informa+on – Conflict of interest – Integrity – Human subject research
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Process of scien6fic wri6ng Hypothesis
Study plan
Experiment
Data processing Results genera+on
Having journal, audience in mind
Wri+ng ar+cle
Submiing
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General Guidelines for Scien+fic Papers: Style and Content
EASE guidelines • Complete, concise and clear • For effec+veness of interna+onal coopera+on all publica+ons should be:
• COMPLETE, CONCISE AND CLEAR!
• IMPORTANT
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• Do not include irrelevant informa+on • Informa+on should not be repeated • Include only necessary tables and figures • Cap+ons – informa+ve but concise • Delete redundancies • Define abbrevia+on at first use • Do not over-‐generalize • Numbers for all numerals
General Guidelines for Scien+fic Papers: Style and Content
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Content
• Study should be planned in advance • The journal and the audience should be chosen
• Informa+on should be organized • All the components of scien+fic ar+cle should be present and sa+sfy the guidelines for a chosen journal
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Repor+ng Guidelines: Content
• Dis+nguish your original ideas • Paraphrase text from other sources • Proper terms (plant community vs. phytocoenosis) • Define every uncommon term • Avoid ambiguity • Be clear what you regard as 100% when repor+ng % • SI units (interna+onal system of units; metric) • Decimal point • Remember that the text will be read by foreigners
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• Make posi+ve, objec+ve asser+ons, directly supported by the results, with necessary qualifica+ons and caveats
• Don’t oversell: “This result clearly proves that the neural network approach is superior and will revolu+onize research methods”.
• Don’t base substan+al claims on unpublished data or on “experience” without objec+ve suppor+ng evidence.
• If you rely on a reference to draw a conclusion, be sure the reference supports the idea, and say where the support may be found in the reference.
Repor+ng Guidelines: Content
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A Dic+onary of Useful Research Phrases • "It has long been known..."
• "It is believed that..." • "It is generally believed
that..." • "A sta+s+cally oriented
projec+on..." • “Typical results are shown” • “Obviously, we will need
addi+onal studies” • “Authors thanks Joe in
conduc+ng experiment and George for helpful comments”
• I didn't look up the original references
• I think • My friends think so, too • Wild guess • Best results are shown • I don’t understand anything • Joe did the work and
George explained it to me
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Example
“In order to provide analy+c control during forensic-‐chemical inves+ga+on, it is customary to use highly sensi+ve and specific analysis methods. Very popular in the prac+ce of chemic-‐toxic studies is the TLC method in view of its accessibility, ease of conduc+ng and expressiveness. Due to the possibility of changing not only sorbents but also solvents, it is possible to quickly solve the problems of separa+on”
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Repor+ng Guidelines: Text Structure
• Simple sentences, should not be very long • Avoid passive voice • Text should be cohesive, logically organized • Each paragraph should start with a topic sentence • Use text tables • Make figures and tables understandable by themselves • Explain your figures and charts, and jus+fy their inclusion. Do not just show them with no stated reason.
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Text tables Original sentence: • Iron concentra+on means (±standard devia+on) were as follows: 11.2±0.3 mg/dm3 in sample A, 12.3±0.2 mg/dm3 in sample B, and 11.4±0.9 mg/dm3 in sample C.
Modified: • Iron concentra+on means (±standard devia+on, in mg/dm3) were as follows: • sample B 12.3±0.2 • sample C 11.4±0.9 • sample A 11.2±0.3
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Replace phrases with a single word
• Considering this fact • In the rela+on to • Exceeding number • In the previous case • In the absence • In large number of cases
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Passive Voice
“Have you ever been told to use passive voice” or
“Did anyone tell you to use passive voice” Examples: • “James Watson was awarded the Nobel Prize for discovering the molecular structure of DNA.“ vs.
• "The Nobel CommiSee awarded James Watson the Nobel Prize for discovering the molecular structure of DNA."
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Passive voice
Nobody takes responsibility in passive voice: “Mistakes were made during the experiment” vs. We made mistakes during the experiment “It is shown in the table” vs. The table shows
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Example
Common dysfunc+on of the immune system was shown in the trials on humans and animals __________________________________ Trials on humans and animals show a common dysfunc+on of the immune system
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Correct Use of Passive Voice
• When the ac+on is more important than the agent of it (as in Materials and Methods)
• In order to emphasize somebody other than the ac+ng agent
• When the agent is unknown
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Repor+ng Guidelines: Language
• Use commonly known words, but not idioma+c expressions
• Define abbrevia+ons (avoid them in abstract) • Spelling • Past tense in body, present in general statements
• Refer to the author as “we” or “I” not “the author”
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Repor+ng Guidelines: Language
Transforma2on of verbs into nouns Obtained es+mates – es+mated Gained improvement-‐ improved Showed growth – grew Made a decision – decided
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Common Fallacies in Wri+ng
• Non Causa Pro Causa Fallacies — No Cause for Cause
• Asempts to establish a causal rela+onship – Cum Hoc, Ergo Propter Hoc – Post Hoc, Ergo Propter Hoc – The Regression Fallacy – Texas Sharpshooter Fallacy
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Fallacies in Wri+ng Cum Hoc, Ergo Propter Hoc — With This, Therefore
• African American popula+on is more likely to experience metabolic consequences of Chronic Kidney Disease (CKD) before reaching the eGFR <60 ml/min threshold … that these observa+ons support a need to adapt clinical prac+ce guidelines shiging screening for CKD to a higher eGFR threshold specifically for African Americans (1)
• The assump6on that the measured clinical parameters in this
representa6ve popula6on are physiologically linked to CKD in African Americans is simplis6c and ignores the effects of a combina6on of gene6c and physiologic adapta6ons superimposed on a background of social and environmental factors that account for minority health dispari6es (2)
• Lesson: Adjustment for possible confounders and other sources of
bias
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Fallacies in Wri+ng Post Hoc, Ergo Propter Hoc — AAer This, Therefore Because of This
• “Since that event followed this one, this event must have caused that one.” It also is referred to as “false cause” or “coincidental correla+on.”
• 7 women in California developed ovarian cysts taking the new mul+phasic oral contracep+ve pills which led to case series report and media prin+ng the story [1].
• No associa6on was shown in follow-‐up studies [2] • Lesson: Checking for possible confounders, conduc+ng valida+on studies before jumping to conclusions, repor+ng on it in wri+ng
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Fallacies in Wri+ng Texas Sharpshooter Fallacy
• In medical research, this fallacy occurs when inves6gators select certain data to demonstrate a cause-‐effect rela6onships.
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Outbreak foci?
Fallacies in Wri+ng The Art of Argumenta
– Argumentum ad Ignoratum (Appeal to Ignorance): Absence of evidence is not evidence of absence
Width of Confidence Interval(±w) Sample Size(n)
0.01 9612
0.02 2403
0.03 1068
0.05 384
0.10 96
0.15 43 Sample sizes required to es2mate a true prevalence of 0.50 with 95% confidence intervals of different widths (±w)
Lesson: Making sure that the sample size is large enough. Recognizing beneficence and non-‐maleficence
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Fallacies in Wri+ng
Argumentum ad Verecundiam (Appeal to Authority): Users of this fallacy ogen call upon the published works of others to bolster their arguments, without ques+oning the accuracy, reliability, or validity of those sources • Quote from an editor as a condi+on for publica+on highlights
the problem: “you cite Leukemia [once in 42 references]. Consequently, we kindly ask you to add references of ar6cles published in Leukemia to your present ar6cle” (1)
• Editors' incen+ve to inflate impact factors through self-‐cita+on
• Survey found that having a tenure posi6on also increased coercion
• Lesson: Being true to your work
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Fallacies in Wri+ng Argumentum ad An;quitatem (Appeal to Tradi2on or History)
“(Talking about acupuncture) I think it is insul+ng to say that Chinese people would carry on with some sort of mys+cal belief when it didn’t work”
“Well, you know – acupuncture is one of those amazing things. I mean it has been around for several thousand years . . . there is a huge amount of validity to what it represents, and there has to be – or it wouldn’t have survived such a long +me “ Lesson: Not making unsupported claims
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7/28/2012
• Argumentum ad Populum (Appeal to the People or Popularity)
• 4 from 5 den+sts recommend sugar-‐free “Trident”“ chewing-‐gum!
• The adver+sement “forgot” to men+on “If pa+ents INSIST to use chewing-‐gum”. They also hid each 5th den+st recommended to avoid the use of chewing-‐gum.
• «Thus based on the assessment of leading Russian clinics “Sangviri+n” is one of the effec+ve modern an+microbial drug of local and common-‐ resorp+ve ac+on for preven+on and treatment of different infec+ous diseases [14–17].»
Fallacies in wri+ng
Fallacies in Wri+ng Myths of Beneficence An analysis of 60 adver+sements that had appeared in the Bri+sh Medical Journal between 1999 and 2001 demonstrated that drug adver+sing uses strong imagery to fabricate mythical associa+ons between medical condi+ons and branded drugs, and that drug adver+sing manipulates readers’ percep+ons by subtle appeal to ancient and modern mythological founda+ons of humanism and Western psychology. 39
Fallacies in Wri+ng
False Dichotomy This is also called a false dilemma, an either-‐or fallacy, fallacy of false choice, or black-‐and-‐white thinking. Most wide-‐spread false dichotomy in scien+fic repor+ng: Sta+s+cal significance P = 0.049 vs. P = 0.051
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Fallacies in Wri+ng Essen2alism Some argument in print or spoken word, some “essen+al feature” is proposed as a defining characteris+c of an otherwise complex issue or larger problem
Each scien+fic specialty looks at disease differently. For example, cancer from the perspec+ve of a general surgeon, a pathologist or an acupuncturist are completely different. Lesson: To be aware of specialized terminology and body of knowledge when repor+ng
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Fallacies in Wri+ng
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Редукционизм Efforts to simplify the problem to the simple rela+ons (O’Connor et al. 2011): “Reduc+onist methods of disease control involve the removal of infec+on or the infec+ous agent, implemen+ng barriers to direct and indirect transmission or by increasing inherent or acquired immunity to the infec+ous agent. However, for those diseases which evade such methods of conven+onal control, a more comprehensive understanding of the complex interac+ons amongst biological (agent and host(s)), environmental, economic and social factors which can affect the emergence and spread of an infec+ous disease is required.”
Things to avoid: • Plagiarism • Fishing expedi+ons – research must be hypothesis driven • Do not plan your study in order to use your results to pool
evidence against the same problem (e.g. meta-‐analyses. • Do not fail to take into account heterogeneity, uncertainty
and dependence • Do not fail to have a robust exploratory data analysis (EDA)
before proceeding into any confirmatory tes+ng (John Tukey teachings)
• Do not discount the importance of internal and external validity when interpre+ng results
• Do not underes+mate the sta+s+cs. The absence of evidence is not the evidence of absence – your study may not have enough power to detect anything unless you have large numbers
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Things that annoy reviewers
– Poor English – Repe++on – Lack of structure in the text – Sentences that are too convoluted and long – Lack of asen+on to detail (a premature drag with typographical errors, etc.)
– Not well thought out statements (make each word count)
– Obscure methods or not well described – Oversta+ng the results – Too long of a paper
44
Repor+ng Guidelines: Structure • IMRaD standard (Introduc+on, Methods, Results, and
Discussion) • Design Specific – EQUATOR network • Journal -‐specific • General:
– Title Page – Conflict of Interest No+fica+on Page – Abstract – Introduc+on – Methods – Results – Discussion – References
45
Standardizing Health Repor+ng EQUATOR (Enhancing Quality and Transparency of Health
Research) network: “Too oaen, good research evidence is undermined by poor
quality repor6ng” • Raising awareness of the crucial importance of good
repor+ng of research • Becoming the recognized global center providing resources,
educa+on and training rela+ng to the repor+ng of health research and use of repor+ng guidelines
• Assis+ng in the development, dissemina+on and implementa+on of repor+ng guidelines
• Monitoring the status of the quality of repor+ng across health research literature
• Conduc+ng research rela+ng to the quality of repor+ng
46
Guidelines for Repor+ng Common Study Types
• CONSORT – Consolidate Standards of Repor+ng Trials
• STROBE – Strengthening the Repor+ng of Observa+onal studies
• STARD – Standards for repor+ng of Diagnos+c Accuracy
• QUOROM – Quality of Repor+ng of Meta-‐analyses (under CONSORT)
47
Example – STROBE checklist Item No Recommendation
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract (b) Provide in the abstract an informative and balanced summary of what was done and what was found
Introduction Background/rationale 2 Explain the scientific background and rationale for the
investigation being reported Objectives 3 State specific objectives, including any prespecified
hypotheses Methods Study design 4 Present key elements of study design early in the paper Setting 5 Describe the setting, locations, and relevant dates,
including periods of recruitment, exposure, follow-up, and data collection
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for the choice of cases and controls Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants (b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed Case-control study—For matched studies, give matching criteria and the number of controls per case
48
Study Designs in Public Health
Experimental (Interven2onal) Studies Observa2onal Studies
Randomized Trials Case reports
Community Trials Case Series
Therapeu+c/Preven+ve Trials Cross-‐sec+onal Studies
Surveillance
Cohort Studies
Case-‐Control
Descrip+ve
Analy+c
49
Observa+onal Descrip+ve Studies
• Case Reports – detailed presenta+ons of a single case or a handful of cases. “Normal Plasma Cholesterol in an 88-‐Year-‐Old Man Who Eats 25 Eggs a
Day — Mechanisms of Adapta+on” [Kern J, NEJM 1991; 324:896–899]
• Case Series –survey of a group of individuals with a par+cular disease performed at a single point of +me. “Pneumocy+s pneumonia: Los Angeles” [MMWR Morbidity and
Mortality Weekly Report 1981;30:250-‐252]
50
Cross-‐Sec+onal Studies
• Describes health of popula+ons (both exposed and non-‐exposed)
• Iden+fies prevalent cases • Finds associa+on, not causa+on • Best-‐suited for lisle disability, pre-‐symptoma+c studies
• Surveys • Good for planning health care
– Na+onal Health Surveys are a good example
51
Surveillance • An ongoing, systema6c collec6on, analysis and interpreta6on of
health-‐related data essen6al to the planning, implementa6on, and evalua6on of public health prac6ce
• Detec+on and no+fica+on of health events • Collec+on and consolida+on of data • Inves+ga+on of cases and outbreaks • Rou+ne Repor+ng • Feedback
U.S. CDC: Ears, EWIDS, NTSIP, ESP, NEDSS, FluNet, BRFSS, FoodNet, etc. Australia: NNDSS U.S.: ProMED, HealthMap Canada: FluWatch, GPHIN France: GPs Sen+nelles Network Asia: APEC EINet WHO: GOARN Europe: MedlSys
52
Case-‐Control Studies
• Comparison of cases versus non-‐cases (controls)
• Retrospec+ve for exposure • Matching all popula+on characteris+cs of cases to those of controls (including biases)
• Mostly for prevalent cases (but could be for incident cases, too)
53
Cohort Studies
• To support the rela+on between the cause and disease
• Presence or absence of risk factor is determined before outcome occurs
• Longitudinal/prospec+ve/incidence studies • Cohorts are free of disease at baseline • Cohorts should be comparable • Diagnos+cs and eligibility should be defined
54
Cohort vs. Case-‐Control
Popula+on
Sample of disease-‐free individuals
Exposed
Not Exposed
Develop Illness
Don’t Develop Illness
Exposed
Not Exposed
Exposed
Not Exposed
Sick
Not Sick
Sick
Not Sick
COHORT STUDY DATA COLLECTION
Case-‐Control Data Collec+on 55
Experimental: Control Study
Controlled: – Inves+gator decides on interven+on
Randomized: – Gold Standard in Epidemiological research – Controls for confounding – Prevents selec+on Bias
Therapeu+c vs. Preven+ve: Pa+ents with Disease vs. Popula+on at Risk
56
Experimental: Controlled Studies
Sample of disease-‐free individuals
Exposed
Not Exposed
Sick
Not Sick
Sick
Not Sick
DATA COLLECTION
Exposure occurs naturally
Inves+gator Determines Exposure
COHORT (Observa+onal)
CONTROLLED (Interven+onal)
57
Randomized Clinical Trial
Experimental Popula+on
Reference Popula+on
• Sample size should be sufficient • Possibility to follow up during the trial • Par+cipants should be informed of risks/ benefits/ blinding/ placebo • Inclusion Criteria
Experimental Popula+on
Reference Popula+on
Study Popula+on
Internal Validity External Validity 58
Randomized Clinical Trial
• Design – Simple – Cross-‐over, factorial
• Sampling • Eligibility criteria • Blinding: single vs. double • Alloca+on: Randomiza+on • Follow-‐up • Analysis • Therapeu+c vs. Non-‐therapeu+c
59
Randomized Trial: CONSORT Flow
Eligible Non-‐eligible Declined
Alloca+on using randomiza+on scheme
Follow-‐up
Included in analysis
60
Protocol of clinical study (typical errors)
• During development of CS protocol: – Fail to jus+fy the study of given drug by the given indica+ons; – Absence of pre-‐clinical and clinical (if applicable) trials; – The objec+ves of study are not listed (primary and secondary
objec+ves), hypothesis of study; – Mixed concep+on of primary objec+ve of study and criteria of
efficacy; – Sta+s+cs! Instead of sample size jus+fica+on and sta+s+cal power:
“the assessment will be performed with PC, Excel, Student’s methods, etc.”;
– Vague procedures and methods, allowing ambiguous interpreta+on; – No dates, no versions
Protocol of clinical study (typical errors)
• While repor+ng of CS:
– Vague descrip+on of study popula+on, that unable the formula+on of conclusion about homoscendacity;
– No sta+s+cal assessment inclusion/exclusion criteria of lost follow-‐up
pa+ents; – No side therapy details and its effect in sta+s+cal analysis; – No severity and resolving of side effects (e.g. 2 pa+ents presented the
head ache – no terms, methods od treatment, outcome, etc.); – No pa+ents’ compliance data; – Separate reports from each center instead of all-‐centers consolidated
report …
General Guidelines For Selec+on of Study Type
Study objec2ve Study type
Study of rare diseases Case control studies
Study of rare exposure, such as exposure to industrial chemicals
Cohort studies in a popula+on group in which there has been exposure (e.g. industrial workers)
Study of mul+ple exposures, such as the combined effect of oral contracep+ves and smoking on myocardial infarc+on
Case control studies
Study of mul+ple end points, such as mortality from different causes
Cohort studies
Es+mate of the incidence rate in exposed popula+ons
Exclusively cohort studies
Study of covariables which change over +me
Preferably cohort studies
Study of the effect of interven+ons Interven+on studies 63
Ecological study
Cross-‐sec2onal study
Case-‐control study
Cohort study(and RCT)
Selec+on bias
N/A 2 3 1
Recall bias N/A 3 3 1
Loss to follow-‐up
N/A N/A 1 3
Confounding 3 2 2 1
Time Required
1 2 2 3
Costs 1 2 2 3
1-‐slight; 2-‐moderate; 3-‐high; N/A= not applicable
Costs of different types of bias for different study designs
64
Introduc+on sec+on
• Iden+fy a gap in knowledge or know-‐how (study problem) o Provide key background (scope/nature/magnitude of the gap) o Be clear that filling this gap will be useful. o Describe the relevant limita+ons of previous studies
• Present your approach to filling the gap (study purpose) o Be clear that your approach is new o Emphasize that your approach addresses the limita+ons of previous studies in a logical and compelling way
Purpose: to convince the reader that your study will yield knowledge or know-‐how that is new and useful
Oaen requires just three paragraphs 65
Introduc+on Checklist Background Statement:
Scope nature magnitude of the gap Be clear that filling the gap is useful
Problem Statement Describe relevant limitations
Study Statement Be clear that your approach is new Emphasize that your approach addresses limitations
Summary Statement Summarizes the study
66
Introduc+on sec+on
• No major difference in introduc+on sec+on between study types
• Some+mes summary statement is omised, or becomes part of the study statement
• STROBE: Introduc+on
Background/ra+onale 2 Explain the scien+fic background and ra+onale for the inves+ga+on being reported
Objec+ves 3 State specific objec+ves, including any pre-‐specified hypotheses
67
Introduc+on sec+on
The next four slides detail the introduc+on checklist process for four separate studies: • Background statement • Problem statement • Study statement
– General descrip+on of the surveillance system
• Summary statement
68
Background Statement:
The treatment of human immunodeficiency virus (HIV) infec+on has undergone considerable change. Protease inhibitors and non–nucleoside-‐analogue reverse-‐transcriptase inhibitors, when used as part of combina+on drug regimens, can profoundly suppress viral replica+on, with consequent reple+on of CD4+ cell counts. Mul+ple clinical trials have shown the virologic and immunologic efficacy of the newer, highly ac+ve an+retroviral-‐drug combina+ons by measuring the plasma load of HIV RNA and CD4+ cell counts. In addi+on, prophylac+c medica+ons are now being used rou+nely to prevent disseminated Mycobacterium avium complex infec+on
Problem Statement
Several reports have described reduc+ons in mortality and in the rate of hospitaliza+on of HIV infected pa+ents; however, such reduc+ons have not been clearly related to specific therapeu+c regimens.
Study Statement We analyzed data collected over 42 months in the HIV Outpa+ent Study. During this period, rates of chemoprophylaxis against opportunis+c infec+on remained rela+vely constant even while paserns of an+retroviral therapy were changing
Summary Statement
This report outlines the changes in death rates and the incidence of opportunis+c infec+ons in a large group of HIV-‐infected outpa+ents, many of whom had previously received extensive treatment.
69
Background Statement:
Among the few diseases claimed to occur more ogen in non-‐smokers than smokers 1 2 that of greatest poten+al importance is Alzheimer's disease, which accounts for most of the demen+as of later life in Britain
Problem Statement
The published epidemiological evidence, although sugges+ve of an inverse rela+on with smoking, is not conclusive either about Alzheimer's disease or demen+a in general. Much of the evidence derives from small retrospec+ve studies of uncertain reliability, many of which excluded vascular demen+a. Prospec+ve studies, in which smoking habits are recorded before the onset of demen+a, should be more informa+ve about the overall effects of smoking, par+cularly if they concern large numbers and prolonged follow up. Only a few such studies have, however, been properly reported (none of which had prolonged follow up)
Study Statement
We sought evidence from the cohort of Bri+sh doctors who have been followed since 1951, with their smoking habits reviewed every six to 12 years.3 4 Many have died from or with some type of demen+a over the past two decades.
Summary Statement
70
Background Statement:
Alcohol was first implicated as a possible risk factor for stroke in 1725(1) Several epidemiological studies now suggest a U-‐shaped associa+on between alcohol intake and stroke(2).
Problem Statement
Previous studies have been cri+cized for not differen+a+ng between nondrinkers who were lifelong abstainers and those who had given up drinking(3-‐7) By asking specifically about previous regular drinking habits we have been able to dis+nguish between the two groups. The level of alcohol consump+on at which this possible protec+ve effect is lost and alcohol becomes a risk factor for stroke are unknown.
Study Statement
We report the findings of a case-‐control study that examines the contribu+on of alcohol to the risk of stroke in moderate and heavy drinkers (both currently and previously), lifelong abstainers (those who have never drunk alcohol), and current abstainers (those who had formerly been regular drinkers but who currently do not drink alcohol), using validated measures of alcohol consump+on.
Summary Statement
71
Background Statement:
Between May 2009 and May 2010, Greece experienced two waves of influenza A(H1N1)2009 transmission
Problem Statement
Given the poten+al for worsening in the clinical severity of influenza during the post-‐pandemic influenza season, as was the case for previous influenza pandemics [7-‐9], it was cri+cal to con+nue surveillance with a focus on severe cases and their clinical characteris+c
Descrip2on of the Surveillance System
In Greece, influenza is annually monitored through the rou+ne sen+nel surveillance system, which became opera+onal in 1999. The sen+nel surveillance system, which covers approximately three percent of the total Greek popula+on in the 2010/11 influenza season, provides data representa+ve of the na+onal popula+on
Summary Statement
This report summarises data from influenza surveillance in Greece during the post-‐pandemic 2010/11 influenza season.
72
Materials and Methods
• Clearly present/define all analysis variables • Organize into logical subsec+ons that illustrate the steps you took to collect, organize, and analyze the data: o Study popula+on o Defini+on of variables o Laboratory methods/ epidemiological inves+ga+on o Interven+on
• Describe what you did, not what you found (Results) • Respect chronology • Describe the original methods in detail; otherwise give references
Purpose: to describe how you collected, organized and analyzed data (relevant to the study purpose)
Length varies depending on originality of methods 73
Materials and Methods – part1 Methods Study design Present key elements of study design early in the paper
Seing Describe the seing, loca+ons, and relevant dates, including periods of
recruitment, exposure, follow-‐up, and data collec+on
Par+cipants and
Seing
(a) Cohort study—Give the eligibility criteria, and the sources and
methods of selec+on of par+cipants. Describe methods of follow-‐up
Case-‐control study—Give the eligibility criteria, and the sources and
methods of case ascertainment and control selec+on. Give the ra+onale
for the choice of cases and controls
Cross-‐sec6onal study—Give the eligibility criteria, and the sources and
methods of selec+on of par+cipants
(b) Cohort study—For matched studies, give matching criteria and
number of exposed and unexposed
Case-‐control study—For matched studies, give matching criteria and the
number of controls per case 74
Variables Clearly define all outcomes, exposures, predictors, poten+al confounders, and effect modifiers. Give diagnos+c criteria, if applicable
Data sources/
measurement
For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group
Bias Describe any efforts to address poten+al sources of bias
Study size Explain how the study size was arrived at
Sta+s+cal
methods
(a) Describe all sta+s+cal methods, including those used to control for confounding (b) Describe any methods used to examine subgroups and interac+ons (c) Explain how missing data were addressed (d) Cohort study—If applicable, explain how loss to follow-‐up was addressed Case-‐control study—If applicable, explain how matching of cases and controls was addressed Cross-‐sec6onal study—If applicable, describe analy+cal methods taking account of sampling strategy (e) Describe any sensi+vity analyses
75
Materials and Methods – part2
Study Design
• Observa+onal or Experimental • Retrospec+ve or Prospec+ve
76
Seing and Par+cipants
• Describe the study popula+on and seing: • Descrip+on should involve relevant demographic, environmental, diagnos+c, comorbid factors
• Defini+on of cohort/case • Exclusion/inclusion criteria • How was consent obtained? • Matching (in case-‐control study)
77
Examples of seing and par+cipants -‐-‐ cohort
The cohort originally comprised 34,439 male doctors on the Bri+sh medical register, resident in the United Kingdom, who had responded to a ques+onnaire about their smoking habits in 1951. Changes in such habits were sought in 1957, 1966, 1972, 1978, 1990, and 1998, and other personal informa+on was sought in 1978, 1990, and 1998. In 1971, follow up was discon+nued for 2459 subjects (10.1% of the survivors) who were living abroad and 218 (0.9%) for other reasons. Almost all of the remaining survivors have con+nued to provide informa+on about their smoking habits*.
Smoking and demen6a in male Bri6sh doctors: prospec6ve study
78
Examples of seing and par+cipants – case control
Cases Three hundred sixty-‐four consecu+ve pa+ents hospitalized for acute stroke in Newcastle upon Tyne between August 1989 and July 1990 formed the study popula+on. No pa+ent refused to take part in the study. Pa+ents were iden+fied by daily contact with the resident medical officer and completeness of case ascertainment was checked with data from the medical records department at each of the three par+cipa+ng hospitals (Freeman Hospital, Royal Victoria Infirmary, and Newcastle General Hospital) Pa6ents with primary subarachnoid hemorrhage were excluded.
Alcohol and stroke. A case-‐control study of drinking habits past and present
79
Examples of seing and par+cipants – case control (con+nued)
Controls Three hundred sixty-‐four community control subjects were matched for age, sex, and family doctor. Control subjects were the next unrelated matching individual to the case in the family doctor register. Control subjects with a previous history of stroke were excluded.
80
Examples of seing and par+cipants – cross sec+onal
The 1997 obligatory health examina+on before school entry evaluated 134,577 children in Bavaria, southern Germany. At the examina+on, the parents of 13,345 children seen in two rural regions were asked to complete a ques+onnaire about risk factors for atopic diseases. Data collected by this ques+onnaire were linked with the data from the school health examina+on. Our analysis was confined to children aged 5 and 6 who had German na+onality.
Breast feeding and obesity: cross sec6onal study
81
Examples of seing and par+cipants – cross sec+onal
The study took place at the an+retroviral therapy clinic of Queen Elizabeth Central Hospital in Blantyre, Malawi, from January 2006 to April 2007. Blantyre is the major commercial city of Malawi, with a popula+on of 1,000,000 and an es+mated HIV prevalence of 27% in adults in 2004.Eligible par+cipants were all adults aged 18 or over with HIV who met the eligibility criteria for an+retroviral therapy according to the Malawian na+onal HIV treatment guidelines (WHO clinical stage III or IV or any WHO stage with a CD4 count <250/mm3) and who were star+ng treatment with a BMI <18.5. Exclusion criteria were pregnancy and lacta6on or par6cipa6on in another supplementary feeding program
Supplementary feeding with either ready-‐to-‐use for6fied spread or corn-‐soy blend in wasted adults star6ng an6retroviral therapy in Malawi: randomised, inves6gator blinded, controlled trial
82
Seing and par+cipants-‐Surveillance
ONGOING OUTBREAK OF WEST NILE VIRUS INFECTION IN HUMANS, GREECE, JULY TO AUGUST 2011
Case-‐Defini2on • A confirmed case is defined as a person mee+ng any of the
following clinical criteria: encephali+s, meningi+s, fever without specific diagnosis and at least one of the four laboratory criteria: (i) isola+on of WNV from blood or cerebrospinal fluid (CSF), (ii) detec+on of WNV nucleic acid in blood or CSF, (iii) WNV-‐specific an+body response (IgM) in CSF, and (iv) WNV IgM high +tre, and detec+on of WNV IgG, and confirma+on by neutralisa+on.
83
Study Variables
• Specify unit of measurement (if applicable) • Quan+fy exposure • Variable transforma+ons • Criteria for defini+ons • Units of +me and special categories
84
Study Variables (examples)
The children's height and weight were measured as part of the rou+ne examina+on. Body mass index was calculated as weight (kg)/(height (m)2). The age specific and sex specific distribu+on of the body mass index among all children with German na+onality in Bavaria, which had been inves+gated during the 1997 school health examina+on, was used as the reference for being overweight (defined as body mass index above the 90th cen6le) or obese (defined as body mass index above the 97th cen6le) because these cen+les were higher than other European reference values.
85
Study Variables (examples) Hypertension was iden6fied by medical history or posi6ve screening results (systolic pressure ≥140 mm Hg). Pre-‐hypertension (asystolic pressure of 120–139 mm Hg) and pre-‐diabetes (a fas6ng blood glucose concentra6on of 6.1–6.9 mmol/L) were defined on the basis of screened laboratory results. Individuals were regarded as regular alcohol drinkers if they consumed two or more alcoholic drinks a day on three or more days a week, and occasional drinkers if they consumed less than regular drinkers.
86
Study Variables (con+nued)
Data from clinic visits were used to calculate the number of days of observa6on per quarter for each pa+ent in each of four categories of prescribed an+retroviral therapy. These categories, in increasing order of intensity, were no an+retroviral therapy, monotherapy, combina+on therapy without a protease inhibitor, and combina+on therapy that included a protease inhibitor. The data collected for each case, using a standardised form, were: demographic characteris+cs (age, sex), dates of admission to the hospital and the ICU, the +me course of illness including the date of symptom onset, underlying condi+ons, complica+ons, use of mechanical ven+la+on support (dates of intuba+on and extuba+on), and an+viral treatment
87
Data Sources/Management
• How the data were collected • If it was part of the registry, describe:
– Original purpose of the database – How large the database is, +meliness – Valida+on, quality checks – Error rate
• Database sogware/hardware • For surveillance paper – a diagram of the surveillance system is preferred
88
Data Sources/Management
Pa+ents (with a close rela+ve or significant other when possible) were interviewed and examined by H.R. (79%) or P.D.A. within 48 hours of hospitaliza+on. Control subjects were interviewed in their homes by H.R. (also with a rela+ve or significant other when possible). Inter-‐observer valida+on studies between the two interviewers were carried out. The propor+on of agreement between two observers, K, was 0.68.
89
Data Sources/Management
Drinking frequency was recorded as a categorical variable, whereas past and present amounts of alcohol consump+on, dura+on of abs+nence, and heavy drinking were recorded as con+nuous variables. Data were transferred to Northumbrian University's Mul6ple Access Computer (NUMAC). Following verifica6on procedures to ensure accurate transcrip6on, data were analyzed using spss-‐x (SPSS-‐X Batch System, SPSS Inc., Chicago, Illinois).
90
• Informa6on in five general categories has been abstracted from the chart for each outpa6ent visit and entered electronically by trained data abstracters; the data are
compiled centrally, reviewed, and corrected before being included in the data base. Because the study physicians are
the source of primary care for these pa+ents, all symptoms, diagnoses, and treatments since the previous visit, are noted
at each clinic visit. The categories of informa+on are as follows: demographic characteris+cs; symptoms; diagnosed diseases; medica+ons prescribed; and laboratory values.
Data Sources/Management
91
Data Sources/Management
92
Study Size
• Specify the null hypothesis and whether it is one or two-‐sided
• Specify the minimum difference in response variable that is considered to be clinically important
• Specify power and alpha level for calcula+ng sample size
93
Examples
To detect a reduc+on in PHS (postopera+ve hospital stay) of 3 days (SD 5 days), which is in agreement with the study of Lobo et al. with a two-‐sided 5% significance level and a power of 80%, a sample size of 50 pa+ents per group was necessary, given an an+cipated dropout rate of 10%. To recruit this number of pa+ents, a 12-‐month inclusion period was an+cipated
94
Examples
Based on an expected incidence of the primary composite endpoint of 11% at 2.25 years in the placebo group, we calculated that we would need 950 primary endpoint events and a sample size of 9650 pa+ents to give 90% power to detect a significant difference between ivabradine and placebo, corresponding to a 19% reduc;on of rela;ve risk (with a two-‐sided type 1 error of 5%)
95
Randomiza+on – Randomized controlled trials (RCT)
Par+cipants should be assigned to comparison groups in the trial on the basis of a chance (random) process characterized by unpredictability
96
Randomized controlled trials (RCT) -‐-‐
examples
• Independent pharmacists dispensed either ac+ve or placebo inhalers according to a computer generated randomiza+on list
• For alloca+on of the par+cipants, a computer-‐generated list of random numbers was used
97
Randomiza+on (con+nued)
• Randomiza+on sequence was created using Stata 9.0 (StataCorp, College Sta+on, TX) sta+s+cal sogware and was stra+fied by center with a 1:1 alloca+on using random block sizes of 2, 4, and 6
• Par+cipants were randomly assigned following simple randomiza+on procedures (computerized random numbers) to 1 of 2 treatment groups
98
Randomiza+on -‐-‐ Concealment
A generated alloca+on schedule should be implemented by using alloca+on concealment, a c r i+ca l mechan i sm that p revents foreknowledge of treatment assignment and thus shields those who enroll par+cipants from being influenced by this knowledge. The decision to accept or reject a par+cipant should be made, and informed consent should be obtained from the par+cipant, in ignorance of the next assignment in the sequence
99
Randomiza+on (concealment)
The doxycycline and placebo were in capsule form and iden+cal in appearance. They were prepackaged in bosles and consecu+vely numbered for each woman according to the randomiza+on schedule. Each woman was assigned an order number and received the capsules in the corresponding pre-‐packed bosle
100
Blinding (RCTs)
The term “blinding” or “masking” refers to withholding informa+on about the assigned interven+ons from people involved in the trial who may poten+ally be influenced by this knowledge. Blinding is an important safeguard against bias, par+cularly when assessing subjec+ve outcomes. EXAMPLE: Whereas pa+ents and physicians allocated to the interven+on group were aware of the allocated arm, outcome assessors and data analysts were kept blinded to the alloca+on.
101
Laboratory Methods(Surveillance)
Serum and CSF specimens were tested for the presence of WNV-‐specific IgM and IgG an+bodies using commercial ELISA kits (WNV IgM capture DxSelect and WNV IgG DxSelect, Focus Diagnos+cs Inc, Cypress, CA, USA). WNV posi+ve specimens were also tested for the presence of other flaviviruses: +ck-‐borne encephali+s virus (TBEV) and dengue virus (DENV).
102
Sta+s+cal Methods
• Describe all sta+s+cal methods, including those used to control for confounding
• Describe the comparisons to be made and the sta+s+cal procedures to be used for making them
• State whether the sta+s+cal analysis will be on the basis of inten+on-‐to-‐treat
• Control for mul+ple tes+ng problem • Report hypothesis power and level (if it is not reported in sampling sec+on)
• Report all required p-‐values and confidence intervals
103
A
В
С
D
Sick Not sick
Expo
sed Not exposed
Cases Controls
No history of disease History of d
isease
Assessment of risk ra+on
A
В
С
D
In case control study the risk ra+on has no outcome, odds ra+on used instead
Repor+ng sta+s+cal methods in Cross-‐Sec+onal studies
• Standard descrip+ve sta+s+cs: -‐Simple prevalence calcula+on
• Prevalence of disease or prevalence of exposure
• Regression to control confounders
105
Cross-‐sec+onal study example: Sta+s+cal Methods
Pa+ent characteris+cs, adjusted for stone history and age, were compared using linear regression for con+nuous covariates and logis6c regression for categorical covariates. Mul6ple linear regression was used to compare mean es+mated GFR between stone formers and non-‐stone formers. Covariates iden+fied as poten+al confounders in the rela+onship between es+mated GFR and stone history were adjusted for. Mul6plica6ve interac6ons between stone history and age, gender, race, diabetes, and BMI were formally tested.
106
Cross-‐sec+onal study example: Sta+s+cal Methods
Mul6nomial logis6c regression was used to compare the rela+ve risk of having an es+mated GFR in a lower category rela+ve to the highest category between persons with and without nephrolithiasis. Model based es+mates are reported as rela6ve risk ra6os comparing stone formers with non-‐stone formers. Adjustment covariates included in the mul+nomial logis+c regression included age, gender, race, BMI, systolic blood pressure, HbA1c, diabetes, history of cardiovascular disease, smoking status, health insurance status, and use of prescrip+on diure+cs.
107
Cross-‐sec+onal study example Sta+s+cal Methods
• The prevalence of overweight and obese children were calculated according to the dura+on of breast feeding. The appropriate χ2 tests were used to compare several items in breas�ed and non-‐breas�ed children and their associa+on with the child being overweight or obese. Logis6c regression models were used to assess the impact of variables that were significantly associated (P<0.05) with both breast feeding and being overweight or obese Confounding was assumed to have occurred if the odds ra6o changed by ≥10%. Confounders and independent risk factors were included in the final logis6c regression model. All calcula+ons were carried out with the SAS sogware package, version 6.12.
108
Sta+s+cal Methods (Case-‐control)
• Comparing groups: – Nominal (chi-‐squared or McNemar’s test) – Ordinal (Wilcoxon, signed-‐rank, Kruskal-‐Wallis, ANOVA)
– Con+nuous (t-‐test, ANOVA) • Odds ra+os – strength of associa+on between exposure and disease is commonly measure by an OR
• Logis+c Regression: to make inference on exposure-‐disease associa+on while adjus+ng for covariates
109
Repor+ng Sta+s+cal Methods in Case-‐Control Study
The Mann-‐Whitney U test was used for between group analyses of nonparametric data, the standard χ2 test when appropriate for discrete variables, and McNemar's χ2 test to compare discordant pairs. The odds ra6o (OR) with 95% confidence intervals (CIs) was used as an es+mate of risk. Log-‐linear analysis was used to calculate the adjusted odds ra+o for poten+al confounding variables.
110
Repor+ng Sta+s+cal Methods in Cohort Studies and Clinical Trials
• Time-‐to-‐event data: Survival func+ons – Describe censored data – Confirm that requirements have been met
• Kaplan-‐Meier analysis • Specify methods to compare two or more survival
curves(log-‐rank or Wilcoxon) • Hazard ra+o • Cox Propor+onal Hazards Model
– Report measure of risk for each variable • Repeated measures(for mul+ple +me points) • ANCOVA for primary and secondary end-‐points • Number of end points
111
Repor+ng Sta+s+cal Methods in Cohort Studies and RCTs
As pre-‐specified, efficacy analyses were performed with the use of a modified inten+on-‐to-‐treat approach, which included the randomized pa+ents and the end-‐point events that occurred ager randomiza+on and no later than the comple+on of the treatment phase of the study (i.e., the global-‐treatment end date), 30 days ager early permanent discon+nua+on of the study drug, or 30 days ager randomiza+on for pa+ents who did not receive a study drug
112
Repor+ng Sta+s+cal Methods in Cohort Studies and RCTs (con+nued)
We used hazard ra6os and two-‐sided 95% confidence intervals to compare the study groups. Rates of the end points were expressed as Kaplan–Meier es+mates through 24 months. Tes+ng was pre-‐specified to occur between the combined-‐dose group for rivaroxaban and placebo at an alpha level of 0.05 on the basis of the log-‐rank test, stra+fied according to the inten+on to use a thienopyridine. If this comparison significantly favored rivaroxaban, then each of the two doses of rivaroxaban was simultaneously compared with placebo with the use of a similar stra+fied log-‐rank test at an alpha level of 0.05 on the basis of the closed tes+ng procedure. Results were examined according to major subgroups for general consistency of treatment effect, and interac+on tes+ng was performed.
113
Repor+ng Sta+s+cal Methods in Randomized Controlled Experiments
The primary endpoint was change in bodyweight during the 20 weeks of the study in the inten+on-‐to-‐treat popula+on … Secondary efficacy endpoints included change in waist circumference, systolic and diastolic blood pressure, prevalence of metabolic syndrome …
114
Repor+ng Sta+s+cal Methods in Randomized Controlled Experiments
We used an analysis of covariance (ANCOVA) for the primary endpoint and for secondary endpoints waist circumference, blood pressure, and pa+ent-‐reported outcome scores; this was supplemented by a repeated measures analysis. The ANCOVA model included treatment, country, and sex as fixed effects, and bodyweight at randomiza+on as covariate. We aimed to assess whether data provided evidence of superiority of each liraglu+de dose to placebo (primary objec+ve) and to orlistat (secondary objec+ve
115
Repor+ng Sta+s+cal Methods in Cohort Studies and RCTs
We calculated hazard ra6os (HR) to compare mortality risks between individuals in different exercise groups (grouped by volume of exercise) and those in the inac+ve group. We used a Cox propor6onate model to analyze categorical and con+nuous variables … The life table method was used to es+mate life expectancy. We calculated adjusted odds ra+os and 95% CIs by comparing the propor+on of individuals mee+ng ac+vity recommenda+ons with the propor+on of those who were inac+ve within each characteris+c group
116
Sta+s+cal Methods -‐ Surveillance
• Exploratory data analysis: – Incidence by age, sex, geography – Trends
• Severity factors • Group comparisons
– Two sample tests, etc. • Event detec+on
– Detec+on methods(+me series/spa+otemporal) – Timeliness – Sensi+vity/Specificity
117
• For early detec+on of localized clusters of dead birds, we used a prospec+ve surveillance system that is based on the spa+al scan sta+s+c (9). This scan sta+s+c uses a circular window to represent poten+al geographic clusters.
• Temporal trends in annual no+fica+on rates of salmonellosis, infec+ous diarrhoea and outbreaks of food-‐borne diseases were assessed using the Cuzick test [9]. Annual rates of salmonellosis and infec+ous diarrhoea were compared between the sexes using the Mann–Whitney test and among age groups using the Kruskal–Wallis test. Post hoc paired comparisons ager the Kruskal–Wallis test were tested using the Mann–Whitney test on each pair of age group and p-‐value adjustment according to Bonferroni’s method [10]
Sta+s+cal Methods -‐ Surveillance
118
Results
• Start with the tables and figures. Write the text later. o Use tables to highlight individual values o Use figures to highlight trends and rela+onships
• Text supplements and reinforces tables and figures o Summarize/emphasize highlights o Fill in gaps (ogen minor)
• Present results in a logical sequence • Describe what you found, not what you did (Methods) • Consider sub-‐sec+ons similar to the ones in Methods • Look to published ar+cles for poten+al templates
Purpose: to describe the results of data analysis that are relevant to the study purpose
119
Results (con+nued) Tables/Figures • Check your math; provide consistent row or column
summa+on. • Keep lines to a minimum; avoid ver+cal lines. • Use footnotes to clarify points of poten+al ambiguity. • Check headings, labels of rows/columns/axes, and footnotes Text • Highlight key rela+onships between dependent/independent
variables. • Present a logical sequence:
o in parallel with methods (consider similar subheadings) o background data → descrip+ve → bivariate → mul+variate
• Make sure all numbers in text are consistent with tables/figures.
Oaen requires just three paragraphs + three tables/figures
120
Tables versus Figures
Tables: beser to use when knowledge of individual values or sta+s+cs are more important than trends and conceptual understanding
1. Title 2. Column/row headings 3. Data fields 4. Footnotes 5. Spanner
121
Five elements of a table
122
Table Title: Example Example 1: Sta+n therapy and cancer recurrence. Example 2:
Effect of daily oral primvasta+n or dorvasta+n on the 4-‐year odds ra+o for the recurrence of prostate and breast cancer. Example 3: The effect of daily oral primvasta+n or dorvasta+n on the 4-‐year odds ra+o (OR) for the recurrence of prostate and breast cancer shows a 3-‐fold lower (P = 0.002) OR for the recurrence of breast cancer for pa+ents receiving primvasta+n (OR = 2.3) versus dorvasta+n (OR = 6.8).
123
Tables : General Recommenda+ons
• Indicate missing data by using a dash, NA, or … • Each footnote should be placed on a separate line at the bosom of the table
• Lesers (or numbers, or symbols) designa+ng footnotes should be ordered alphabe+cally (or numerically)
• The symbol designa+ng a footnote that applies to the en+re table should be placed ager the +tle
124
Table Alignment
• The stubs should be all leg jus+fied • In the columns/data fields, words should be leg jus+fied and whole numbers right-‐jus+fied
• Data fields containing decimal points, plus/minus symbols, slashes, hyphens, or parentheses should be aligned on these elements.
• When the text in a stub wraps to a second line, the corresponding data field should align with the top line of the stub.
125
A. Annual per capita healthcare expenditures.
Expenditure, $
Israel 1971
Madagascar 36
Sweden 2828
Yemen 82
Zimbabwe 149
B. Annual per capita healthcare expenditures.
Expenditure, $
Israel 1971
Madagascar 36
Sweden 2828
Yemen 82
Zimbabwe 149
C. Annual per capita healthcare expenditures.
Expenditure, $
Sweden 2828
Israel 1971
Zimbabwe 149
Yemen 82
Madagascar 36
Table alignment example
126
Tables, column formats example
Mean (SD), mg/L
Mean ± SD, mg/L
Deviation from target, %
Pig serum 11.4 (2.1) 11.4 ± 2.1 14 Sheep serum 10.7 (1.4) 10.7 ± 1.4 7 Artificial serum 10.3 (0.8) 10.3 ± 0.8 3
Saline 10.1 (0.6) 10.1 ± 0.6 1 Human serum 9.9 (0.6) 9.9 ± 0.6 −1 Cow serum 9.6 (1.4) 9.6 ± 1.4 −4 Horse serum 8.9 (0.7) 8.9 ± 0.7 −11
Table 3. Phenytoin concentrations measured by immunoassay for matrices supplemented with 10 mg/L phenytoin.#
Two different styles of presen2ng results 127
What is the right size?
• 60 characters for half-‐page, 120 for full • For a 2-‐column journal, 110 characters would fit onto a portrait-‐formased page.
• Otherwise journal might publish landscape • Re-‐orient if number of column headings : row headings greater 2:1
• If only one p-‐value out of the whole column is significant – remove and place a not in a footnote
• Use abbrevia+ons when journals permit it • Split into 2
128
Example : Table Too Wide
Age, years
Undifferentiated leukemia
, %
Myeloblastic
leukemia, %
Promyelocytic
leukemia, %
Myelomonocytic
leukemia, %
Monocytic
leukemia, %
Erythroleukemia,
%
Microkaryoblasti
c leukemia
, %
Megakaryoblastic leukemia
, %
<21 91 80 85 81 82 73 62 52
21–40 89 83 79 77 68 61 57 41
41–60 74 62 68 59 40 37 31 24
>60 51 48 39 34 28 21 16 9
Table 5. Age-related 5-year survival for forms of acute myelogenous leukemia.#
129
Table, re-‐oriented
AML type Age
<21 Years 21–40 Years 41–60 Years >60 Years
Undifferentiated, % 91 89 74 51
Myeloblastic, % 80 83 62 48
Promyelocytic, % 85 79 68 39
Myelomonocytic, % 51 48 39 34
Monocytic, % 82 68 40 28
Erythroleukemia, % 73 61 37 21
Microkaryoblastic, % 62 57 31 16
Megakaryoblastic, % 52 41 24 9
Table 7. Age-‐related 5-‐year survival for forms of acute myelogenous leukemia (AML)
130
Formaing tables, con+nued
Study No. of
patients
Leukocyte count, %a Day 0
Day 7
Day 14
Day 21
Day 28
Day 56
Day 84
Wilkins and Potter, Refb11 M11;F11 100 97 — 84 — — 70
Pillsbury et al., Ref 12 M10;F18 100 100 81 — 76 — 64
Annesley et al., Ref 18 M27;F20 100 89 76 — 63 — 62
Kronnenberg and Stenmeyerson, Ref 20 M9;F7 100 103 95 — 88 69 —
Flowers and Peterson, Ref 25 M20;F23 100 101 96 93 89 86 98
Flloyd et al., Ref 26 M27;F23 100 95 — — 91 — 79
Robinson et al., Ref 27 M19;F20 100 — 100 — 96 — 94
Nowicki and Phillips, Ref 32 M15;F16 100 — 92 — 82 74 —
Table 6. Previous studies of leukocyte reduction during kelvac therapy in patients with chronic myelogenous leukemia.#
Are these columns necessary? 131
Figures • Proper+es of a good graph:
– Draws asen+on to the data and not the graph – The symbols and connec+ng lines are easy to read – Axis number and labels are easy to read – The lengths of the two axes are balance ( 1:1.3) – The scales used on each axis match the range – Tick marks are used appropriately – The legend is clear and concise – Self-‐sufficient – The data deserve to be graphed
132
Common Mistakes
Plasma vs. serum sodium for paired specimens from 150 pa2ents. (A), x-‐ and y-‐axis scales of 0–165 mmol/L; (B), x-‐ and y-‐axis scales of 120–170 mmol/L; (C), Bland–Altman plot.
133
Using appropriate axis interval
134
Why include this graph?
135
Results vs. Data Figure 1 shows the survival rates following diagnosis and ini+a+on of treatment in the 3 treatment groups. At 6 months the survival rates were 95% for the A group, 91% for the B group, and 39% for the radia+on-‐treated group. At 12 months the rates were 83%, 69%, and 23%;, at 18 months 74%, 17%, and 15%; and at 24 months were 70%, 11%, and 9%.
Data but no results
Figure 1 shows the survival rates following diagnosis and ini+a+on of treatment in the 3 treatment groups. At 6 months the survival rates were significantly higher in the A and B treatment groups compared with the radia+on-‐treatment group. At 12, 18, and 24 months the survival rates in the A group exceeded those of both the B and radia+on-‐treatment groups.
Results, but no data
136
Results vs. Data
Six months ager diagnosis and ini+a+on of treatment, the survival rates for the A and B groups were 2.4 and 2.3 +mes higher, respec+vely, than the radia+on treatment group (both P < 0.001), but survival rates were not found to differ between the A and B groups (P = 0.56) (Figure 1). By 12 months, however, pa+ent survival in the A group was 1.2 +mes higher than in the B group (P = 0.031), and 4.3 and 6.4 +mes higher at 18 and 24 months (both P <0.001).
137
Results and only the Results
We compared the death rates for the 262 healthy controls with those of the 203 conges6ve heart failure pa6ents over a 2-‐year period. Survival curves were generated with the Masterson mortality index formula. The conges+ve heart failure group was found to have a significantly higher short-‐term mortality rate.
When the 2-‐year survival curves for healthy controls and conges+ve heart failure pa+ents were compared, the conges+ve heart failure group was found to have a significantly higher short-‐term mortality rate.
138
Using modern graphics and visualiza+on
Using modern graphics and visualiza+on
Penn-‐state university: mul+-‐purpose map with +me and spa+al flu cases distribu+on support
Using modern graphics and visualiza+on
Red – anger, blue – dissa+sfac+on, yellow – joy, emo+ons in blog community
Использование современных графиков и методов визуализации
Popula+on distribu+on by countries
Results -‐ Key Tables • Study flow • Comparison between study and control group at baseline (so
groups are comparable) – Give characteris+cs of study par+cipants (e.g. demographic, clinical, social) and informa+on on exposures and poten+al confounders
– Cohort study—Summarise follow-‐up +me (e.g., average and total amount)
• Primary comparison table – (cohort, RCT) Report absolute (and rela+ve) differences for primary endpoints
– (cohort, RCT) Report 95% CI for primary endpoints – (case-‐control)Report numbers in each exposure category, or summary measures of exposure
– (cross-‐sec+onal) Report numbers of outcome events or summary measures
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Results -‐ Key Tables (con+nued) • Main Results:
– Give unadjusted es+mates and, if applicable, confounder-‐adjusted es+mates and their precision (e.g., 95% confidence interval). Make clear which confounders were adjusted for and why they were included
– Report category boundaries when con+nuous variables were categorized
– If relevant, consider transla+ng es+mates of rela+ve risk into absolute risk for a meaningful +me period
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Results Checklist Par+cipants Report number of individuals at each
stage of the study • Consider flow diagram • Give reasons for non-‐par+cipa+on
Baseline Data Baseline demographic and clinical characteris+cs for each group
Variables/Outcomes Report numbers of outcome events or summary measures over +me
Main results Give unadjusted es+mates and if applicable, confounder-‐adjusted es+mates and their precision.
Adverse effects (for Experimental Designs)
Readers need informa+on on poten+al harm as well as benefit
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Results examples
T h e n e x t s e v e r a l s l i d e s demonstrate different ways to present results
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Results: CONSORT Flow
Eligible Non-‐eligible Declined
Alloca+on using randomiza+on scheme
Follow-‐up
Included in analysis
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Results – sample study flow
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Results – baseline comparison
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Results: Primary outcome (RCT)
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Results – primary outcomes (RCT)
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Results: Primary outcome (RCT)
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Results – primary outcome (cohort)
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Primary outcome (alterna+ve figure)
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Primary Efficacy End Point (RCT)
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Results – primary outcome (Cross-‐sec+onal)
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Regression with primary outcomes (Cross-‐sec+onal study)
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Results – Regression with Odds-‐Ra+os
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Results-‐Report Adverse Effects
“The propor+on of pa+ents experiencing any adverse event was similar between the rBPI21 [recombinant bactericidal/permeability-‐increasing protein] and placebo groups: 168 (88.4%) of 190 and 180 (88.7%) of 203, respec+vely, and it was lower in pa+ents treated with rBPI21 than in those treated with placebo for 11 of 12 body systems … the propor+on of pa+ents experiencing a severe adverse event, as judged by the inves+gators, was numerically lower in the rBPI21 group than the placebo group: 53 (27.9%) of 190 versus 74 (36.5%) of 203 pa+ents, respec+vely. There were only three serious adverse events reported as drug-‐related and they all occurred in the placebo group.”
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Discussion
• Dis+ll the essence of your study o Re-‐state key results o State main conclusion
ü Be clear about why results support the conclusion ü Maintain connec+on with the purpose of the study
• Interpret your study in the context of the literature o Compare with results of/methods used in related studies o Emphasize strengths of your study and what is new
• State limita+ons/caveats (frankly, without apology) • Make recommenda+ons
o Changes in prac+ce/policy o Future studies, including some specifics (e.g. study method)
Purpose: to interpret your results and jus+fy your interpreta+on
Oaen requires just four or five paragraphs 160
Discussion Checklist Dis2ll the essence of study
a. Restate key results b. State main conclusion
-‐ Be clear about why results support the conclusion. -‐ Maintain connec2on with purpose of the study.
Interpret your study in the context of the literature a. Compare with results of/methods used in related studies b. Emphasize strengths of your study, and what is new
State limita2ons/caveats (use examples) Discuss limita2ons of the study, taking into account sources of poten2al bias or imprecision. Discuss both direc2on and magnitude of any poten2al bias
Make recommenda2ons a. changes in prac2ce/policy b. future studies, including some specifics (e.g. study method)
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Discussion (Examples) During periods of seasonal influenza ac+vity, we found moderately ac+ve (1.5–2.9 METs/day) and ac+ve (≥3.0 METs/day) individuals to be approximately 15% less likely to have an influenza-‐coded physician office or emergency department visit compared to inac+ve individuals. When stra+fied by age, we observed similar findings among individuals <65 years but not ≥65 years Among individuals <65 years, moderately ac+ve and ac+ve individuals were not more likely than inac+ve individuals to visit physicians for non-‐influenza-‐related condi+ons such as derma++s or periodic health examina+ons during influenza season…
KEY RESULTS
MAIN CONCLUSIONS
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Discussion (Examples)
Aging is linked to declines in the ability to defend against pathogens [40], and has been associated with increased morbidity and mortality from infec+ous diseases in the elderly [40]–[41]. Addi+onally, age-‐related declines in immune response to influenza vaccines are well documented [42]–[44]. The reduced immune func+on of the elderly may prevent them from receiving any immune system benefits from physical ac+vity. [Comparison with other studies]
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Discussion (Examples) To our knowledge, this is the first epidemiologic study that has examined the rela6onship between physical ac6vity and influenza-‐related morbidity during seasonal influenza epidemics. Previous studies have mostly focused on upper respiratory tract infec+ons (URTIs) with an emphasis on athletes [4], and only a few focused on the general popula+on [12], [19], [45]. Our finding of a 15% reduc+on in influenza-‐coded outpa+ent visits is similar to the 20% reduc+on in URTIs observed in popula+on-‐based studies, although those studies used self-‐reported outcome measures [12], [19], [45]. Only one other study assessed the associa6on between physical ac6vity and influenza, and the outcome was influenza-‐associated mortality [9]. Although a beneficial effect was found, our study suggests a protec6ve effect at a much earlier stage than mortality.
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Discussion (Examples) -‐ limita+ons
This study had several limita+ons. First, our outcome measure was influenza-‐coded outpa6ent visits rather than laboratory-‐confirmed influenza infec6ons, which would be the most ideal outcome measure
A second limita+on is that measurement of physical ac6vity and certain covariates relied on self-‐report, and verifica6on of subject responses was not possible First, we are limited in our ability to adequately es+mate an associa+on between stone history and renal func+on in young adults due to a lack of data on stone formers less than age 30
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Discussion -‐ Recommenda+ons
Future research should ideally use laboratory-‐confirmed influenza outcomes to confirm the associa+on between physical ac+vity and influenza infec+on. Public health authori+es and clinicians should work toward a common goal of increasing physical ac+vity and the public’s awareness of its benefits. These ac+ons may help to mi+gate the health and economic burden caused by influenza.
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Discussion -‐ Recommenda+ons Further work in alternate study samples is needed to validate this finding and to determine the mechanisms for the associa+on between kidney stones and decreased GFR. However, this is the first study to show such a connec+on in a na+onally representa+ve sample of the United States popula+on. Given our observa+ons, the serious nature of renal disease and the increasing incidence of nephrolithiasis in the United States, further inves+ga+on is warranted.
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Abstract
Purpose: to highlight key points from major sec+ons of the ar+cle
Emphasize what is new and useful
Component Abstracted from
Major purpose of study Introduc+on
Basic procedures Methods
Main findings Results
Principal conclusions Discussion
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Synopsis – Find weaknesses
Reliability of information about risk factors of chronic diseases collected in Missouri through the Behavioral Risk Factors Surveillance System. Synopsis (initial version) The Behavioral Risk Factors Surveillance System is widely used by health care authorities of the States to measure the prevalence of risk factors of chronic diseases. Despite its extensive utilization, only a few studies that assess reliability and validity of collected data have been conducted. A double testing study was carried out in the State of Missouri to assess reliability of information collected through the System. Authors repeatedly interviewed 222 people by phone, who passed full interview in March-April 1993. The repeated interview was conducted after 6-30 days following the first one. Repeatability of results was high for demographic data (kappa 0.85-1.00). Reliability of information about chronic diseases and risk factors thereof was also high. Kappa values ranged from 0.82 for the question about hypertension up to 1.00 for the question about smoking at that moment. In respect of the cancer survey procedures the reliability was lower for the knowledge of prostate cancer detection tests (kappa 0.21), than the tests used to diagnose cancer in women (mammography and smears). The question about attitude to smoking showed lower reliability than the question about actions to combat smoking. In general our data demonstrate flexibility of the System and its applicability to collecting information.
The Behavioral Risk Factors Surveillance System is widely used by health care authorities of the States to measure the prevalence of risk factors of chronic diseases. We carried out a double testing study to assess reliability of information collected through the System in the State of Missouri. We repeatedly interviewed 222 people by phone, who passed full interview in March-April 1993. The repeated interview was conducted after 6-30 days following the first one. Repeatability of results was high for demographic data (kappa 0.85-1.00). Reliability of information about chronic diseases and risk factors thereof was also high. Kappa values ranged from 0.82 for the question about hypertension up to 1.00 for the question about smoking at that moment. In respect of the cancer survey procedures the reliability was lower for the knowledge of prostate cancer detection tests (kappa 0.21), than the tests used to diagnose cancer in women (mammography and smears). The question about attitude to smoking showed lower reliability than the question about actions to combat smoking.
Synopsis – Published version: Find weaknesses
Introduction. Although tests to detect blood in feces are widely used to diagnose rectal cancer, there are no evidences that such use can result into decrease of mortality of this type of cancer. We conducted a randomized survey of the use of the method and showed its efficiency. Methods. 46,551 participants of the survey aged 50-80 were randomly selected either for the control group or for one of the test groups. The rectal cancer screening was carried out once a years in the first group, and once in two years in the second one. Those with positive test results passed through additional examination, including colonoscopy. Mortality statistics were collected for all participants over 13 years observation period. A group of experts determined causes of death, and an autopsist (pathologist) determined a stage of cancer for each case. Variations in mortality of rectal cancer were assessed by special statistical methods. Results. Total mortality of rectal cancer over the 13 year period was worth 5.88 per 1,000 (95% confidence interval 4.61-7.15) in the annually screened group, 8.44 (95% confidence interval 6.82-9.84) in the biannually screened group, and 8.83 (95% confidence interval 7.26-10.40) in the control group. This indicator in the first screened group (not the second one) was certainly lower as compared to the control group. This group showed detection of cancer at earlier stage, and the forecast of the survival rate in patients was better along with decrease of mortality. Conclusions. Annual tests to detect blood in feces decreased total mortality of rectal cancer by 33% within 13 years.
DECREASE OF MORTALITY OF RECTAL CANCER BY IMPLEMENTATION OF SCREENING FOR BLOOD IN FECES
Structured Synopsis
Finalizing the paper and submission
• Drag a +tle • Wri+ng and edi+ng process • Picking a journal • Last sec+ons :
– References – Special men+on
• Transla+on
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Title
What goes into the +tle? • The topic (T) – study subjects and seing
o Who, what, when, where
• In addi+on, chose one or two among: o M – Methods o R – Results o C – Conclusions o N – name of study or data set
Purpose: to provide a brief, informa+ve summary that will asract your target audience
Highlight what is new and useful 173
Title examples
Title • Longitudinal evalua6on of prostrate-‐
specific an6gen levels in men with and without prostrate disease
o An injury preven+on program in an African-‐American community
• Smoking, pregnancy, and source of pre-‐natal care: Results from the Pregnancy Risk Assessment Monitoring System
o Reduc+on of high-‐risk sexual behavior among heterosexuals undergoing HIV an+body tes+ng: A randomized clinical trial
T M R C N
• + + o + • + + o + + ?
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Massive mailing does not effect the use of vaccines among MedicAir Medical insurance recipients Nurses stress factors in neonatal Intensive Case Units: American Study Experience and sa+sfac+on of primary care, secondary Analysis with mul+level modeling HIV mortality and infec+vity in India: assessment of na+onal-‐representa+ve census 1.1 mln of residents
Title T M R C N
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Examples of +tles: Your opinion?
Racial difference of Survival with Oral cancer in Georgia Time of experiment implementa+on: Racial difference of Survival with Oral cancer in Georgia: 1978-‐2001 Which race(s) under higher risk? Reduced survival among Afro-‐American pa+ents with oral cancer in Georgia: 1978-‐2001 The analysis controlled the major risk factors: Reduced survival among Afro-‐American pa+ents with oral cancer in Georgia ager Risk Factors Control: 1978-‐2001 Data source? Reduced survival among Afro-‐American pa+ents with oral cancer in Georgia ager Risk Factor Control: Georgia Registra+on Index SEER, 1978-‐2001 The higher risk limited by several subgroups of Afro-‐American pa+ents: Reduced survival among subgroups of Afro-‐American pa+ents with oral cancer in Georgia ager Risk Factor Control: Georgia Registra+on Index SEER, 1978-‐2001
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Bri2sh Medical Journal (BMJ): The +tle must include study design if presented as an original study American Journal of Preven2ve Medicine Title must be brief but informa+ve, underline but not describe, serve as a shortcut but not an offer, reflect what was done, do not use verbs, include nouns for easier search, do not use symbols or abbrevia+ons ICMJE (Interna2onal Commidee of Medical Journals Editors) : Short +tles easier to read. Too short +tles may lack the informa+on about, for example, the study design. Authors encouraged to include all possible informa+on into the +tle which will make the search more sensible and relevant.
Title requirements
Wri+ng the ar+cle and submiing it to a journal
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Wri+ng and submiing the ar+cle • Conduct literature review • Start the paper! • Conduct study/analyze data • Organize/summarize results succinctly • Get early, frequent feedback (in pieces) • Formulate your key message • Apply the “new/useful” test • Choose your target audience • Choose your target journal • Read journal instruc+ons to authors
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Wri+ng and submiing the ar+cle • Drag (and debug) an abstract • Write the first drag • Master the literature • Relearn, rethink, and rewrite • …and rewrite, rewrite, rewrite • How long? • Cri+cally review and finalize the abstract • Asend to the details • Submit ar+cle to the target journal • Have a “Plan B”
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Conduct literature review
• Google scholar • PubMed – try “Single Cita+on Matcher” • Web of Knowledge • NIH-‐funded research (RePORTER) • Contact leading inves+gators to learn about in-‐press or unpublished work
• Scopus • Medline.ru • Elibrary.ru
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Start the paper!
• Yes, even before you do the study • Drag the introduc+on – perhaps borrow from a study protocol or grant proposal that you already wrote
• Drag dummy table shells and figure axes for Results
• Decide which sta+s+cal methods you may need – may dictate study design
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Conduct study/analyze data
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Organize/summarize results succinctly
• Fill in dummy tables and figures with real data
• Drag addi+onal tables and figures if needed – look at published ar+cles for poten+al templates
• Summarize each table or figure in a single sentence
184
Get early, frequent feedback (in pieces)
• Ask coauthors/colleagues if your tables/figures and text summaries are clear/concise/compelling
• Give presenta+ons to colleagues and at conferences
• The more hurdles you clear before you submit your paper to a journal, the fewer you will be asked to clear during the review process
• Don’t wait for a complete drag to begin geing feedback
185
Formulate your key message
• Keep it simple; try to boil down to a single sentence
• Your message must contain something new and useful
• Make sure your results support your key message
• The message may change as you develop the paper
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Apply the “new/useful” test
• Journal editors are interested in new informa+on that is useful to their target audience
• Does your study meet these criteria? • If not, the effort of wri+ng a manuscript may not be warranted
• If yes…
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Choose your target audience
What audience is most interested in your message?
o Clinicians? o Public health prac++oners? o Basic scien+sts? o A broad audience?
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Choose your target journal
• Journal impact factor • Select based on:
o Match with target audience o Strength of your ar+cle
• Consider aiming high – reviewer comments from a high-‐level journal can be valuable
• However, aiming high with data that are geing “stale” is risky
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Read journal instruc+ons to authors
• Find your target journal “instruc+ons for authors” on the Internet or in an issue of the journal
• Is your key message relevant to the target journal’s mission statement?
190
Drag (and debug) an abstract
• Check for internal consistency o Logical flow from Purpose to Methods to Results to Conclusion?
o Conclusion consistent with the Purpose?
• If you see flaws in the Abstract, ask yourself: o Do I need to do addi+onal analyses? o Addi+onal literature review? o Addi+onal thinking?
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Write the first drag
• Write for your target audience (use appropriate terminology or jargon)
• Consider using an outline • Don’t spend too much +me on the grammar, syntax, or details (only you need to understand the first drag)
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Master the literature
• As you obtain feedback, colleagues will direct you to new references
• Update your PubMed Single Cita+on Matcher search
• Russian Scien+fic Cita+on Index • (and/or local UZ equivalent)
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Relearn, rethink, and rewrite
• As you master the literature, you will see your work in a new light
• Transmit this new thinking to your manuscript
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… and rewrite, rewrite, rewrite
• Most papers require at least five drags, maybe ten – save and date them all
• You may need to revise your key message • Perhaps consider changing target audience, target journal
• Perhaps your paper is now beser than you ever imagined, and you want to aim for a higher-‐circula+on/impact journal
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How long?
• How long should your manuscript be? • Follow guidance in target journal’s instruc+ons for authors
• “Shorter papers get luckier faster”
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Cri+cally review and finalize the abstract
• Check again for internal consistency (as described previously)
• Make sure the abstract is fully consistent with the body of the ar+cle
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Asend to the details
• Carefully review and comply with target journal’s instruc+ons for authors
• Call/e-‐mail the journal if you s+ll have ques+ons
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Submit ar+cle to target journal
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Have a Plan B
Decide on your next target journal in case you receive a rejec+on
200
About the importance of opportunity and impact
• As to how being opportunis+c can lead to high acceptability of research grants and scien+fic outputs (examples of bioterrorism research in the US ager 2001, or the large number of papers and research that focus on Q fever, for example, ager the outbreak in the Netherlands).
• But watch out because the search for high impact publica+ons can lead to “miscarriages” (the case of Wakefield)
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Wri+ng for Grant Proposals
Eugene Elbert, MS Johns Hopkins University, U.S.A.
August 2012
Phases of Grant Wri+ng
1. Planning 2. Preparing 3. Writing 4. Submitting
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1. Planning
• Research funder’s program areas and priorities. – What other projects have been funded?
• Read the instructions! • For a specific RFP (request for proposals), READ
the RFP! • Does your project match the funder’s needs? • Do you have the capacity to do the proposed
project? • Be familiar with the submission process
– Is there an online submission process?
2. Preparing
• Develop your idea – Is it new? Interes+ng? – What are the specific aims? – What is your research design? – What will the outcomes be?
• What will it take to make it successful? – Who will lead the project? – Who else will be involved?
• Internal staff and external partners – How long will it take to accomplish? – How much money will it take?
2. Preparing (con+nued)
• Get organized – Read the RFP again – Is a leser of intent (LOI) needed before the full proposal can be submised?
• Develop a +meline for wri+ng the grant proposal – Be aware of deadlines. Start early!
• Assign roles in the proposal process – Will different people write different parts?
206
3. Wri+ng
• Follow direc+ons – Are you including everything as requested? – Pay asen+on to format and page limits.
• Make it easy for the reviewer to read – Be clear and concise – Use buzzwords that will stand out and show your work is aligned with the funder’s goals and mission.
– Do not use jargon – Spell out abbrevia+ons and acronyms
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3. Wri+ng (con+nued)
• Title – Make it interes+ng and clear – Does it capture what you will do? – Look at +tles of other projects the funder has funded for format
• Know the review process – How will the proposal be scored? – Is one part more important than another?
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What the customer wants…
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Innova+on • New methods for old problems (examples) • Old methods (elsewhere) for old problems (examples)
• Any method for new problems (BE THE FIRST) o First papers, no maser how precarious become seminal ones (1)
(1) Ugbomoiko et al. 2008. Parasites of importance for human health in Nigerian dogs: high prevalence and limited knowledge of pet owners. BMC Vet Research.
Parts of a Grant Proposal
NOTE: These are are different for different funders – read the instructions! 1. Cover leser 2. Summary or abstract 3. Problem or Needs statement 4. Project descrip+on
• Introduc+on • Objec+ves • Methods
5. Evalua+on 6. Key personnel 7. Budget
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The Sec+ons
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1. Cover leder – One page leser addressed to the funding source
and signed by the highest official
2. Summary or abstract 3. Problem or Needs Statement
– State the problem with facts and evidence that support the need for your project.
– Be sure to use accurate data.
The Sec+ons (con+nued)
4. Project Description – Introduc2on
• Provide history of organiza+on and experience of your team
• How does this work fit into what has been done previously by you and others?
– Objec2ves • List 2-‐4 Specific Aims of the project • Define the measurable outcomes of your program.
– Methods • What ac+vi+es that will take place to achieve the objec+ves?
• What is the research design?
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The Sec+ons (con+nued)
5. Evalua2on – How you will measure the success of your project? – Plan for con+nua+on beyond the grant period
6. Key personnel – Describe the people needed to do project – What are the qualifica+ons of the project director and others?
– What are their roles on the project ( Director, Program Manager, Sta+s+cian, etc.
7. Budget – How much will it cost to conduct the project? – Be aware of funding limits-‐ do not ask for more than they are giving out
– Provide jus+fica+on of costs 213
4. Submiing
• Review your work – Have you followed instructions? – Ask someone from outside of your team to
review your proposal to get a new perspective • Revise
– Correct any errors – Make as clear and concise as possible
• Submit – Follow directions
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More Informa+on
Grant Wri+ng Tips Sheet [hsp://grants1.nih.gov/grants/grant_+ps.htm] Common Grant Applica+on (Na+onal Network of Grantmakers) [hsp://www.nng.org/cga.html] EPA Purdue University Grant-‐Wri+ng Tutorial (Environmental Protec+on Agency) [hsp://www.purdue.edu/envirosog/grants/src/msieopen.htm] Sample proposals: [hsp://www.npguides.org/guide/sample_proposals.htm] Grants and Grant Proposal Wri+ng (St. Louis University) [hsp://eweb.slu.edu/papers2/grant01v32e.pdf] All About Grants Tutorials (Na+onal Ins+tutes of Health) [hsp://www.niaid.nih.gov/ncn/grants/default.htm]
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