Gutkin S.W. Writing high-quality medical publications: a user 's manual

Boca Raton: CRC Press, 2019. — 507 p.Copyright Page
DedicationBetween You and Me
ConclusionsAuthor
Acknowledgments: Image Credits
Frontmatter
Principles and examples of quality in medical communications
Get Your Paper Published—On the First Attempt!
Common Reasons Why Papers Are Rejected and Strategies to Promote Acceptance
Unique Challenges for Medical Writers
Principles and Examples of Ethical Medical Communications
Fair balance (the foremost principle of quality) is the coin of our realm
Fair balance culminates an open, free, and two-way (or “multi-way”) collaboration
Fair balance in the planning process
Fair balance by study report section
Fair-Balanced Introduction
Fair-Balanced Methods
Fair-Balanced Results
Fair-Balanced Discussion
Fair-Balanced Conclusions
Other Pillars of Quality in Medical Writing
Brevity
Lead with the News!
Check your Gunning Fog Index
Clarity
Methods sections as the “Rosetta Stone” of manuscript clarity
Cogency
Thesis statement and topic sentences
A Caveat
Topic Sentences
Overall Guidance on Cogency
Variety
Integrity
On the other hand! Thorny factors that continue to breach integrity
Lack of meaningful author participation
Potential undue influence by a study sponsor
The Dreaded “P Word”
Other failures to disclose
Credibility and fidelity
Chapter SummaryChapter : Drafting the manuscript: Step-by-step guidelines and exercises
Work Flow Dynamics
Getting started
Managing the flow of work
Structure and Style
Finding your voice: From Charles Darwin to Chris Matthews
Examples of both evidence-based and memorable prose
Structuring the Outline
“Scaffolding”: The Gutkin × cogent manuscript structure outlineMethods
Internal fidelity: “Rule of Chekhov’s Gun”
Results
Discussion
Before-after exercises in discussions (and results)
Conclusions
How To Write A Report of a … (“HOW–TWA–ROA”) Study
Overview
HOW–TWA–ROA … Systematic literature review (SLR) or meta-analysis
Considerations When Conducting a Systematic Literature Review or Meta-Analysis and Interpreting the Findings
HOW–TWA–ROA … Randomized controlled trial (RCT)Methods
Results
Discussion
HOW–TWA–ROA … Observational study
OverviewMethods
Results
Discussion
HOW–TWA–ROA … Health economic and outcomes research (HEOR) studyMethods
Rhetorical Exercises and “Before-After” Examples to Enhance Prose Style
Motivation
Overview
Brevity
Concise “ma non troppo”
Variety
General prose style
Before-after examples on general prose style from my practice
Before-After Exercises, by Manuscript Segment
Article title
Abstract
”Help Readers to Find Your Article”
Acknowledgments: Before and after editingTables: Before and after editing
Putting it all together: A representative (fictitious) study report for a multispecialty journalAppendix: “Diction-Err-Y”— A guide to better usage
“Diction-Err-Y”: Of “plural effusions” and other peculiarities of medical writing’s “singular” syntax and semantics
Chapter : Biostatistics: Issues in study design, analysis, and reporting
Statistics: Sturm und Drang
Micro … Starting small
The nature and distributions of data and their implications for statistical analyses
Signal versus noise*; Confidence versus doubt
Statisticians are frequentists (unless they are Bayesian!)
Overview of study designs: What we can and cannot (or should not) say in fair-balanced discussion sections
The fundamentals: Descriptive statistics, including data distributions and measures of central tendency and dispersion (error)
Data distributions and their contours
Measures of central tendency
Arithmetic mean
Geometric mean
Mode
Median
Measures of dispersion (“error”)
Standard Deviation (SD)
Variance
Standard error of the mean (SEM)
% Confidence interval (CI)
Converting % CI to SE and SD
Interquartile Range (IQR)
Degrees of freedom (df)
Statistical error
Types and Errors
Types and Errors and fundamentals in computing sample size
What p values signify (and don’t)
Human error: Defects in logic
The null hypothesis as an example of “plausible reasoning”
Problems with logic: Denying the antecedent and affirming the consequent
Post hoc ergo propter hoc (“after this, therefore because of this”)
Introduction to confounding and bias
Confounding
Simpson’s Paradox and Lord’s Paradox
Regression to the mean (RTM) and maturation effects
Comprehensive review of precision, reproducibility, reliability, validity, effect modification, interaction, and bias
Effect modification
Interaction
Prominent forms of bias
Overview
Selection bias
Information bias
Other issues
Statistical tests for categorical data: Examples and exercises
Paired data
McNemar’s test
Unpaired Data
Fisher’s exact test (FET) or Fisher’s exact test of contingency–
χ (Chi-squared) test
Cochran–Mantel–Haenszel (CMH)  test,
χ Test of heterogeneity
Statistical tests for continuous data: Examples and exercises
Parametric tests
Student’s (Gosset’s) t-test (smaller samples) or z-test (larger samples) (paired)Half Title
Title Page
Copyright Page
DedicationBetween You and Me
Conclusions
References
Author
Acknowledgments: Image Credits
Frontmatter
Chapter
Chapter
Chapter
Chapter : Principles and examples of quality in medical communications
Get Your Paper Published—On the First Attempt!
Common Reasons Why Papers Are Rejected and Strategies to Promote Acceptance
Unique Challenges for Medical Writers
Principles and Examples of Ethical Medical Communications
Fair balance (the foremost principle of quality) is the coin of our realm
Fair balance culminates an open, free, and two-way (or “multi-way”) collaboration
Fair balance in the planning process
Fair balance by study report section
Fair-Balanced Introduction
Fair-Balanced Methods
Fair-Balanced Results
Fair-Balanced Discussion
Fair-Balanced Conclusions
Other Pillars of Quality in Medical Writing
Brevity
Lead with the News!
Check your Gunning Fog Index
Clarity
Methods sections as the “Rosetta Stone” of manuscript clarity
Cogency
Thesis statement and topic sentences
A Caveat
Topic Sentences
Overall Guidance on Cogency
Variety
Integrity
On the other hand! Thorny factors that continue to breach integrity
Lack of meaningful author participation
Potential undue influence by a study sponsor
The Dreaded “P Word”
Other failures to disclose
Credibility and fidelity
Chapter SummaryChapter : Drafting the manuscript: Step-by-step guidelines and exercises
Work Flow Dynamics
Getting started
Managing the flow of work
Structure and Style
Finding your voice: From Charles Darwin to Chris Matthews
Examples of both evidence-based and memorable prose
Structuring the Outline
“Scaffolding”: The Gutkin × cogent manuscript structure outlineMethods
Internal fidelity: “Rule of Chekhov’s Gun”
Results
Discussion
Before-after exercises in discussions (and results)
Conclusions
How To Write A Report of a … (“HOW–TWA–ROA”) Study
Overview
HOW–TWA–ROA … Systematic literature review (SLR) or meta-analysis
Considerations When Conducting a Systematic Literature Review or Meta-Analysis and Interpreting the Findings
HOW–TWA–ROA … Randomized controlled trial (RCT)Methods
Results
Discussion
HOW–TWA–ROA … Observational study
OverviewMethods
Results
Discussion
HOW–TWA–ROA … Health economic and outcomes research (HEOR) studyMethods
Rhetorical Exercises and “Before-After” Examples to Enhance Prose Style
Motivation
Overview
Brevity
Concise “ma non troppo”
Variety
General prose style
Before-after examples on general prose style from my practice
Before-After Exercises, by Manuscript Segment
Article title
Abstract
”Help Readers to Find Your Article”
Acknowledgments: Before and after editingTables: Before and after editing
Putting it all together: A representative (fictitious) study report for a multispecialty journalAppendix: “Diction-Err-Y”— A guide to better usage
“Diction-Err-Y”: Of “plural effusions” and other peculiarities of medical writing’s “singular” syntax and semantics
Chapter : Biostatistics: Issues in study design, analysis, and reporting
Statistics: Sturm und Drang
Micro … Starting small
The nature and distributions of data and their implications for statistical analyses
Signal versus noise*; Confidence versus doubt
Statisticians are frequentists (unless they are Bayesian!)
Overview of study designs What we can and cannot (or should not) say in fair-balanced discussion sections
The fundamentals: Descriptive statistics, including data distributions and measures of central tendency and dispersion (error)
Data distributions and their contours
Measures of central tendency
Arithmetic mean
Geometric mean
Mode
Median
Measures of dispersion (“error”)
Standard Deviation (SD)
Variance
Standard error of the mean (SEM)
% Confidence interval (CI)
Converting % CI to SE and SD
Interquartile Range (IQR)
Degrees of freedom (df)
Statistical error
Types and Errors
Types and Errors and fundamentals in computing sample size
What p values signify (and don’t)
Human error: Defects in logic
The null hypothesis as an example of “plausible reasoning”
Problems with logic: Denying the antecedent and affirming the consequent
Post hoc ergo propter hoc (“after this, therefore because of this”)
Introduction to confounding and bias
Confounding
Simpson’s Paradox and Lord’s Paradox
Regression to the mean (RTM) and maturation effects
Comprehensive review of precision, reproducibility, reliability, validity, effect modification, interaction, and bias
Effect modification
Interaction
Prominent forms of bias
Overview
Selection bias
Information bias
Other issues
Statistical tests for categorical data Examples and exercises
Paired data
McNemar’s test Unpaired Data
Fisher’s exact test (FET) or Fisher’s exact test of contingency- χ (Chi-squared) test
Cochran–Mantel–Haenszel (CMH)  test
χ Test of heterogeneity
Statistical tests for continuous data: Examples and exercises
Parametric tests
Student’s (Gosset’s) t-test (smaller samples) or z-test (larger samples) (paired)
One-way analysis of variance (ANOVA); F test,
Further background on, and implications of, ANOVA: Regression analysis, general linear model, two-factor ANOVA, repeated-measures ANOVA, and ANCOVA
ANCOVA
Special examples of ANOVA
Factorial ANOVA
­­ Multivariate ANOVA (MANOVA)
Repeated-Measures ANOVA (rmANOVA)
Nonparametric tests
Wilcoxon Signed-Rank (WSR) and Rank Sum (WRS) tests
Wilcoxon signed-rank (WSR) test
Wilcoxon rank sum (WRS) test
Friedman test
Mann–Whitney U test
Kruskal–Wallis (K–W) test
Selected statistical tests organized in ascending alphabetical order
ANCOVA See above (as an extension of ANOVA)
Bayesian statistics
Bland–Altman (B−A) Plot,
Bootstrapping
Correlation
Correlation : Pearson’s product-moment correlation (coefficient = r),
Correlation : Spearman’s rank correlation (coefficient = ρ)
Correlation : Kendall’s correlation (coefficient = τ)
Funnel plot
General linear model (including regression models), generalized linear model, generalized linear mixed model (GLMM), and generalized estimating equation (GEE),
General linear models
Heterogeneity
Hosmer and Lemeshow’s test, (goodness of fit in predictive models)
Imputation
Kolmogorov and Smirnov’s (K–S) and Shapiro and Wilk’s (S–W) tests, and data normality
Propensity score matching (PSM)
Principal component analysis (PCA)
Regression analyses
Risk concepts: Toward a more nuanced understanding
Number needed to treat to harm
Survival analyses: Kaplan–Meier (K–M) and proportional hazards (PH) (or Cox regression) methodsChapter : Best practices: Consensus recommendations and standards to prepare high-quality, ethical, transparently disclosed manuscripts for journal publication
Executive summary
Part : QC checklists and other tables to optimize manuscript quality
Part : Forms Related To Transparent And Ethical Disclosures
FormForm
Form
Form A
Form BAppendix : Minimum clinically important differences (MCIDs) in patient-reported outcomes (PROs)Appendix : Probability distribution data tables to compute p values
Appendix : Common abbreviationsa in clinical and pharmaceutical sciences
Index One-way analysis of variance (ANOVA); F test ,
Further background on, and implications of, ANOVA: Regression analysis, general linear model, two-factor ANOVA, repeated-measures ANOVA, and ANCOVA
ANCOVA
Special examples of ANOVA
Factorial ANOVA
Multivariate ANOVA (MANOVA)
Repeated-Measures ANOVA (rmANOVA)
Nonparametric tests
Wilcoxon Signed-Rank (WSR) and Rank Sum (WRS) tests
Wilcoxon signed-rank (WSR) test
Wilcoxon rank sum (WRS) test
Friedman test
Mann–Whitney U test
Kruskal–Wallis (K–W) test
Selected statistical tests organized in ascending alphabetical order
ANCOVA See above (as an extension of ANOVA)
Bayesian statistics
Bland–Altman (B−A) Plot,
Bootstrapping
Correlation
Correlation : Pearson’s product-moment correlation (coefficient = r),
Correlation : Spearman’s rank correlation (coefficient = ρ)
Correlation : Kendall’s correlation (coefficient = τ)
Funnel plot
General linear model (including regression models), generalized linear model, generalized linear mixed model (GLMM), and generalized estimating equation (GEE),
General linear models
Heterogeneity
Hosmer and Lemeshow’s test, (goodness of fit in predictive models)
Imputation
Kolmogorov and Smirnov’s (K–S) and Shapiro and Wilk’s (S–W) tests, and data normality
Propensity score matching (PSM)
Principal component analysis (PCA)
Regression analyses
Risk concepts: Toward a more nuanced understanding
Number needed to treat to harm
Survival analyses: Kaplan–Meier (K–M) and proportional hazards (PH) (or Cox regression) methodsChapter : Best practices: Consensus recommendations and standards to prepare high-quality, ethical, transparently disclosed manuscripts for journal publication
Executive summary
Part : QC checklists and other tables to optimize manuscript quality
Part : Forms Related To Transparent And Ethical Disclosures
FormForm
Form
Form A
Form BAppendix : Minimum clinically important differences (MCIDs) in patient-reported outcomes (PROs)Appendix : Probability distribution data tables to compute p values
Appendix : Common abbreviationsa in clinical and pharmaceutical sciences