RESEARCH: 

Professor Evans scholarly contributions include applied and methodological research published in reputable journals such as the New England Journal of Medicine (NEJM), JAMA, the Annals of Internal Medicine, Lancet, BMJ, Clinical Infectious Diseases, the Journal of Clinical Oncology, AIDS, Stroke, Pain, Statistics in Medicine, Clinical Trials, and Statistics in Biopharmaceutical Research.

As a thought leader in clinical research methodologies, Professor Evans emphasizes the importance of thoroughly understanding the research questions (Evans et.al. Statistics in Biopharmaceutical Research, 2021). A transcript of a recent talk the FDA Statistical Association was recently published describing how many recent “innovations” compromise scientific rigor and lower the evidentiary bar, urging deeper thought regarding the most important clinical questions, and proposing increased interest on questions of a pragmatic origin to match their clinical importance and utility (Evans et.al., Statistics in Biopharmaceutical Research, 2022).

Leadership in Clinical Research Collaborations

Professor Evans serves as the Director of the Statistical and Data Management Center (Huvane et.al. Clinical Infectious Diseases, 2017) for the Antibacterial Resistance Leadership Group (ARLG), collaborative clinical research network that prioritizes, designs, and executes clinical research to reduce the public health threat of antibacterial resistance. He has led several infectious disease collaborations including: (1) a Phase II trial that implemented a Simon’s two-stage optimal design which concluded that oral etoposide was effective for treating relapsed or progressed AIDS-associated Kaposi’s sarcoma (Evans et.al., Journal of Clinical Oncology, 2002), (2) a randomized trial evaluating a therapy for the treatment of HIV-associated neuropathic pain, innovatively measured by an electronic diary using random prompts (Evans et.al., PLOS ONE, 2007), (3) a study of the agreement between methods of measuring LDL cholesterol in HIV (Evans et.al., HIV Clinical Trials, 2007), and (4) a study evaluating the prevalence and risk factors for peripheral neuropathy in HIV disease (Evans et.al., AIDS, 2011). Collaborations in other disease areas include serving on the Executive Committee for the acute stroke or transient ischemic attack treated with aspirin or ticagrelor and patient outcomes (SOCRATES) (Johnston et.al. NEJM, 2016) and Acute Stroke or Transient Ischaemic Attack Treated with Ticagrelor and ASA [acetylsalicylic acid] for Prevention of Stroke and Death (THALES) (Johnston et.al., NEJM, 2020).

Benefit:risk Assessment

Randomized trials are the gold standard for evaluating intervention effects. Diagnostic studies with appropriate reference standards are the quintessential model for evaluating classification accuracy. However, studies often fail to provide the necessary evidence to inform medical decision-making. The important implications of these deficiencies are largely absent from discourse in medical research communities. Motivated by pragmatism, Professor Evans and colleagues are developing benefit:risk methodologies to inform patient management.

Typical analyses of clinical trials involve intervention comparisons for each efficacy and safety outcome. Outcome-specific effects are estimated and potentially combined in benefit:risk analyses believing that this informs the totality of effects on patients. However, such approaches do not incorporate associations between outcomes, are confounded by competing risks, and since efficacy and safety analyses are often conducted on different analysis populations, the population to which these analyses apply, is unclear.

Professor Evans proposed the desirability of outcome ranking (DOOR) (Evans, et.al. Clinical Infectious Diseases, 2015) and partial credit methodologies described in “Using Outcomes to Analyze Patients Rather than Patients to Analyze Outcomes: A Step toward Pragmatism in Benefit:risk Evaluation” (Evans et.al., Statistics in Biopharmaceutical Research, 2016) as a remedy to these issues. The methods can incorporate patient values and estimate personalized effects. The methods were used to compare ceftazidime-avibactam vs. colistin for the treatment of infections due to CRE (van Duin, et.al., Clinical Infectious Diseases, 2017), a pathogen characterized as having an urgent hazard level by the CDC and as a Priority 1 (Critical) pathogen by the WHO. The methods were also implemented in the acute stroke or transient ischemic attack treated with aspirin or ticagrelor and patient outcomes (SOCRATES) trial, a multicenter, randomized, double-blind, double-dummy, parallel-group trial conducted at 674 sites in 33  countries between January 2014 and October 2015 (Evans et.al., Clinical Trials, 2020). Recently, the FDA implemented the DOOR ORISE Fellowship.

Diagnostic Study Collaboration and Methods

Typical antimicrobial susceptibility testing (AST) takes 48-72 hours, critically delaying appropriate therapy. Rapid diagnostics are needed. Professor Evans and colleagues are evaluating the use of rapid molecular diagnostics to inform clinical decision-making with emphasis on the World Health Organization’s (WHO) three Priority 1 (critical) pathogens: carbapenem-resistant Enterobacteriaceae (Evans et.al., Clinical Infectious Diseases, 2015), Acinetobacter baumannii (Evans et.al., Journal of Clinical Microbiology, 2016), and Pseudomonas aeruginosa (Evans et.al., Clinical Infectious Diseases, 2016).

Professor Evans was the senior author on the Antibacterial Resistance Leadership Group (ALRG) proposal master protocol for evaluating multiple infection diagnostics (MASTERMIND) (Patel et.al. Clinical Infectious Diseases, 2017) for advancement of infectious diseases diagnostics. MASTERMIND uses a single subject’s sample(s) to evaluate multiple diagnostic tests simultaneously, providing efficiencies of specimen collection and characterization. MASTERMIND offers central trial organization, standardization of methods and definitions, and common comparators. The Antibacterial Resistance Leadership Group recently implemented the design in a study resulting in the FDA’s first clearance of two diagnostic tests for extragenital testing for chlamydia and gonorrhea.

Standard evaluation of diagnostics consists of estimating sensitivity, specificity, and positive/negative predictive values and likelihood ratios. However, these measures have limited utility for guiding clinical decision-making. Diagnostic utility depends on prevalence and the relative importance of potential errors (false positive vs. false negative). Professor Evans and colleagues proposed benefit-risk evaluation of diagnostics: a framework (BED-FRAME) (Evans, et.al. Clinical Infectious Diseases, 2016) and average weighted accuracy (AWA) (Liu et.al., Clinical Infectious Diseases, 2019), for pragmatic diagnostic evaluation. They defined weighted accuracy and diagnostic yield measures to communicate the expected clinical impact of diagnostic application and the tradeoffs of diagnostic alternatives. The methods were used to design and analyze a study evaluating the utility of a host response-based diagnostic test categorizing acute respiratory tract illness into bacterial, viral, or neither etiology in a regulatory setting.

The complexities of antibiotic resistance mean that successful stewardship must consider both the effectiveness of a given antibiotic and the spectrum of that therapy to minimize imposing further selective pressure. Professor Evans and colleagues developed the Desirability of Outcome Ranking approach for the Management of Antimicrobial Therapy (DOOR MAT), a flexible quantitative framework that evaluates the desirability of antibiotic selection to aid the evaluation of diagnostics and stewardship strategies (Wilson et.al. Clinical Infectious Diseases, 2020)

Methodologies for Interim Monitoring of Clinical Trials

Dr. Evans is the Editor of a Statistical Mini-Series "Independent Oversight of Clinical Trials: Protecting Patients and Scientific Integrity" for the New England Journal of Medicine (NEJM) Evidence (Evans, NEJM Evidence, 2022). The series describes the need for independent oversight in clinical trials and discuss principles, concepts, and complexities of stopping trials for efficacy, futility, harm, and landscape changes through examples.

Professor Evans has published on the presentation of benefits and risks to aid interim monitoring (Evans et.al. Annals of Internal Medicine, 2020). He and colleagues introduced use of prediction for data monitoring of clinical trials and as a valuable tool for DSMBs (Evans et.al. DIJ, 2007; Li et.al., Stat in Biopharm Res, 2009). The methods are the foundation for the commercial software EAST PREDICT.

Strategy Clinical Trials

Patient management of patients with bacterial infections is not a single decision but a dynamic process, based on a sequence of decisions with therapeutic adjustments made over time. Adjustments are personalized, tailored to individual patients as new information becomes available. However, strategies allowing for such adjustments are infrequently studied. Traditional antibiotic trials are often nonpragmatic, comparing drugs for definitive therapy when drug susceptibilities are known. Professor Evans and colleagues developed COMparing Personalized Antibiotic StrategieS (COMPASS), a trial design that compares strategies consistent with clinical practice, decision-rules that guide empiric and definitive therapy decisions. Sequential Multiple Assignment Randomized Trials (SMART) COMPASS (Evans et.al. Clinical Infectious Diseases, 2019; Yin et.al., CHANCE, 2020)) allows evaluation when there are multiple definitive therapy options. SMART COMPASS is pragmatic, mirroring clinical antibiotic treatment decision-making and addressing the most relevant issue for treating patients: identification of the patient-management strategy that optimizes ultimate patient outcomes. SMART COMPASS is valuable in the setting of antibiotic resistance when therapeutic adjustments may be necessary due to resistance.

Goodness of Fit Tests

Many studies utilize binary outcomes, e.g., success vs. failure. Often clusters of correlated observations arise through repeated measurements or other mechanisms (e.g., measurements on people within the same family). Logistic regression models utilizing generalized estimating equations and mixed/random-effects evaluate outcomes accounting for the correlation. Dr. Evans developed goodness-of-fit tests in logistic mixed/random-effects models and logistics GEE models (Evans, et.al. Comm in Stat, 2004a; Evans, et.al. Comm in Stat, 2004b; Evans et.al. Stat in Med, 2005). The methods are now widely applied.

Educational and Guidance Contributions

Professor Evans was a member of the Presidential Task Force on P-values and Statistical Significance of the American Statistical Association (ASA). The task force published a statement guiding the use of p-values (Benjamini et.al. Annals of Applied Statistics, 2021). Professor Evans offered comments on the use of p-values to improve statistical practice (Evans, Stat in Biopharm Res, 2021).

Professor Evans has published educational papers for medical researchers on important statistical concepts. For example, comparisons of protocol-defined to published endpoints revealed that many trials have changed endpoints. Dr. Evans developed guiding principles for modification to trial endpoints after trial initiation (Evans SR. PLOS Clinical Trials, 2007). He and colleagues have recently published papers: (1) describing issues in the selection of the analysis population in anti-infective clinical trials (Evans et.al., Stat Comm in Inf Dis, 2018), (2) evaluating whether non-randomized controls can be used to evaluate anti-infective drugs in the resistant-pathogen setting (Evans et.al., Stat Comm in Inf Dis, 2017), (3) discussing adaptive clinical trial designs in healthcare epidemiology research (Huskins et.al., Clinical Infectious Diseases. 2017), (4) discussing methods and issues in studies of CRE (Evans, et.al., Virulence, 2016), and (5) describing alternatives for event-time data analyses that are more robust than standard methods (Uno et.al., Annals of Internal Medicine, 2015). He has published several educational papers on clinical trial concepts including: fundamentals of clinical trial design (Evans, J Exp Stroke Trans Med, 2010), clinical trial structures (Evans, J Exp Stroke Trans Med, 2010), and common statistical concerns in clinical trials (Evans, J Exp Stroke Trans Med, 2010). He recently published guidance for the use of real world data for planning eligibility criteria and enhancing recruitment (Evans et.al. Therapeutic Innovation & Regulatory Science, 2021).

Professor Evans has authored three books including a textbook on clinical trials, Fundamentals for New Clinical Trialists (2016). Two statistical methodology books were co-authored with colleagues based on a series of papers from our research group: (1) Sample Size Determination in Clinical Trials with Multiple Endpoints (2015), and (2) Group-Sequential Clinical Trials with Multiple Co-Objectives (2016).

Interviews of Professor and his work can be found here:

1. Internationally Recognized Leader in Clinical Trials, Biostatistics, and Infectious Disease Research Joins the George Washington University.  https://publichealth.gwu.edu/content/internationally-recognized-leader-clinical-trials-biostatistics-and-infectious-disease. 2018.
2. How can Novel Statistical Methods Tackle Antibiotic Resistance? Interview with Scott Evans. Cytel Blog. http://www.cytel.com/blog/novel-statistics-antibiotic-resistance-scott-evans. 2017.
3. Q&A with Scott Evans, CHANCE Executive Editor. American Statistical Association. http://www.amstat.org/ASA/Publications/Q-and-As/Scott-Evans.aspx.
4. Outsmarting Superbugs. Plymouth Magazine. https://www.plymouth.edu/magazine/alumni-green/outsmarting-superbugs/. 2016.
5. Superbugs: An Epidemic Begins. Harvard Magazine. http://harvardmagazine.com/2014/05/superbug. 2014.
6. Stats + Stories on NPR: Superbug Statistics. https://statsandstories.net/health1/superbug-statistics. 2019.
7. Stats + Stories on NPR: Sports Statistics. https://soundcloud.com/statsandstories/sports-stats-in-2019/s-Fidnl. 2019.

Sites of Note

JOURNALS

CHANCE
Statistical Communications in Infectious Diseases

BOOKS

Fundamental Concepts for New Clinical Trialists
Sample Size Determination in Clinical Trials with Multiple Endpoints
Group-Sequential Clinical Trials with Multiple Co-Objectives

PUBLICATIONS: 

1. Evans SR. Independent Oversight of Clinical Trials through Data and Safety Monitoring Boards. NEJM Evidence. 2022.
2. Evans SR. Radical Thinking: Scientific Rigor and Pragmatism: A Transcript of Professor Scott Evans’ Invited Seminar to the FDA Statistical Association. Statistics in Biopharmaceutical Research. 2022.
3. Evans SR. Our Most Important Discovery: The Question. Statistics in Biopharmaceutical Research. 2021.
4. Evans SR. Paraoan D, Perlmutter J, Raman SR, Sheehan JJ, Hallinan ZP. Real‑World Data for Planning Eligibility Criteria and Enhancing Recruitment: Recommendations from the Clinical Trials Transformation Initiative. Therapeutic Innovation & Regulatory Science. https://doi.org/10.1007/s43441-020-00248-7. 2021.
5. Evans SR. Waking up to p: Comment on “The Role of p-Values in Judging the Strength of Evidence and Realistic Replication Expectations”, Statistics in Biopharmaceutical Research, 13:1, 19-21, DOI: 10.1080/19466315.2020.1811151. 2021.
6. Benjamini Y, De Veaux RD, Efron B, Evans S, Glickman M, Graubard BI, He X, Meng XL, Reid NM, Stigler SM, Vardeman SB, Wikle CK, Wright T, Young LJ, Kafadar K. ASA President’s Task Force Statement on Statistical Significance and Replicability. The Annals of Applied Statistics. Vol. 15, No. 3, 1084–1085. https://doi.org/10.1214/21-AOAS1501. © Institute of Mathematical Statistics, 2021.
7. Hamasaki T, Hung HMJ, Hsiao, CF, Evans SR. On selecting the critical boundary functions in group-sequential trials with two time-to-event outcomes. Contemporary Clinical Trials. https://doi.org/10.1016/j.cct.2020.106244. 2021.
8. Chambers HF, Evans SR, Patel R, Cross HR, Harris AD, Doi Y, Boucher HW, van Duin D, Tsalik EL, Holland TL Pettigrew MM, Tamma PD, Hodges KR, Souli M, Fowler Jr VG. Antibacterial Resistance Leadership Group 2.0 – Back to Business. Clinical Infectious Diseases. 2021.
9. Yin X, Hamasaki T, Follmann D, Evans SR. OutSMARTing Superbugs. CHANCE, September, 2020.
10. Yin X, Hamasaki T, Evans SR. Sequential, Multiple-Assignment, Randomized Trials for COMparing Personalized Antibiotic StrategieS (SMART-COMPASS): Design Considerations for Selecting the Optimal Treatment. Statistics in Biopharmaceutical Research. 2020.
11. Johnston SC, Amarenco P, Denison H, Evans SR, Himmelmann A, James S, Knutsson M, Ladenvall P, Molina CA, Wang Y. Ticagrelor and Aspirin versus Aspirin in Acute Ischemic Stroke or TIA. N Engl J Medicine. 2020.
12. Evans SR, Knutsson M, Amarenco P, Albers GW, Bath PN, Denison H, Ladenvall P, Jonasson J, Easton JD, Minematsu K, Molina CA, Wang Y, Wong KSL, Johnston SC. Methodologies for pragmatic and efficient assessment of benefits and harms: application to the SOCRATES trial. Clinical Trials, Vol. 17(6) 617–626, 2020.
13. Evans SR, Bigelow R, Chuang-Stein C, Ellenberg S, Gallo P, He W, Jiang Q, Rockhold F. Presenting Risks and Benefits: Helping the Data Monitoring Committee Do Its Job. Annals of Internal Medicine. 2020.
14. Liu Y, Tsalik EL, Jiang Y, Ko ER, Woods CW, Henao R, Evans SR. Average Weighted Accuracy (AWA): Pragmatic Analysis for a RADICAL Study. Clin Infect Dis.; 2020.
15. Sugimoto T, Hamasaki T, Evans SR, Halabi S. Group-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes. Lifetime Data Anal. 2020.
16. Evans SR, DeGruttola V. Innovations in Design, Education, and Analysis (IDEA) Introduction. Clin Infect Dis.; 2019;68(11):1960.
17. Jiang Y, Follmann D, Evans SR. Superbug Clinical Trials. Wiley StatsRef-Statistics Reference Online. 2019.
18. Evans SR, Follmann D, Liu Y, Holland T, Doernberg SB, Rouphael N, Hamasaki T, Jiang Y, Lok JL, Tran TTT, Harris AD, Fowler, Jr. VG, Boucher H, Kreiswirth BN, Bonomo RA, van Duin D, Paterson DL, Chambers H. Sequential Multiple Assignment Randomized Trials for COMparing Personalized Antibiotic StrategieS (SMART-COMPASS). Clin Infect Dis. 2019;68(11):1961–7. PMID: 30351426 PMC Journal - In Process
19. Evans SR, Tran TTT, Hujer AM, Hill CB, Hujer KM, Mediavilla JR, Manca C, Domitrovic TN, Perez F, Farmer M, Pitzer KM, Wilson BM, Kreiswirth BN, Patel R, Jacobs MR, Chen L, Fowler Jr VG, Chambers HF, Bonomo RA; Antibacterial Resistance Leadership Group (ARLG). Rapid Molecular Diagnostics to Inform Empiric Use of Ceftazidime/Avibactam and Ceftolozane/Tazobactam against Pseudomonas aeruginosa: PRIMERS IV. Clin Infect Dis. 2019;68(11):1961–7. PMID: 30351426 PMC Journal - In Process
20. Evans, SR, Rubin DB, Powers JH, Follmann D. Analysis Populations in Anti-infective Clinical Trials: Whom to Analyze? Stat Commun Infect Dis. 2018; NIHMSID 988165
21. Hamasaki T, Evans SR, Asakura K. Design, data monitoring, and analysis of clinical trials with co-primary endpoints: a review. J Biopharm Stat. 2018; 28(1):28-51. PMID: 29083951 PMCID: PMC6135538
22. Huskins WC, Fowler Jr VG, Evans SR. Adaptive Designs for Clinical Trials:  Application to Healthcare Epidemiology Research. Clin Infect Dis. 2018; 66(7):1140-46. PMID: 29121202 PMCID: PMC6018921
23. Van Duin D, Lok JJ, Earley M, Cober E, Richter SS, Perez F, Salata RA, Kalayjian RC, Watkins RR, Doi Y, Kaye KS, Fowler Jr VG, Paterson DL, Bonomo RA, Evans SR. Colistin vs. Ceftazidime-avibactam in the Treatment of Infections due to Carbapenem-Resistant Enterobacteriaceae. Clin Infect Dis. 2018; 66(2):163-171. PMID: 29020404 PMCID: PMC5850032
24. Evans SR, Powers J. Evaluating Anti-Infective Drugs in the Resistant Pathogen Setting: Can we Use External Controls? Stat Commun Infect Dis. 2017; 9(1): 20160003. PMID: 28757914 PMCID: PMC5529043 
25. Patel R, Tsalik EL, Petzold E, Fowler Jr. VG, Klausner JD, Evans SR. Antibacterial Resistance Leadership Group (ARLG). MASTERMIND: Bringing Microbial Diagnostics to the Clinic. Clin Infect Dis. 2017; 64(3):355-360. PMID: 27927867 PMCID: PMC5894935
26. Huvane J, Komarow L, Hill C, Tran TT, Pereira C, Rosenkranz S, Finnemeyer M, Earley M, Jiang HJ, Wang R, Lok J, Evans SR; Statistical and Data Management Center of the Antibacterial Resistance Leadership Group (ARLG). Fundamentals and Catalytic Innovation: The Statistical and Data Management Center of the Antibacterial Resistance Leadership Group. Clin Infect Dis. 2017; 64(suppl_1):S18-S23. PMID: 28350899 PMCID: PMC5848245
27. Chambers HF, Cross HR, Evans SR, Kreiswirth BN, Fowler Jr VG; Antibacterial Resistance Leadership Group (ARLG). The Antibacterial Resistance Leadership Group: Progress Report and Work in Progress. Clin Infect Dis. 2017; 64(suppl_1):S3-S7. PMID: 28350896 PMCID: PMC5850447
28. Sugimoto T, Hamasaki T, Evans SR, Sozu T.  Sizing clinical trials when comparing bivariate time-to-event outcomes. Stat Med. 2017; 36(9):1363-1382. PMID: 28120524 PMCID: PMC5533151
29. Evans SR, Harris AD. Methods and issues in studies of CRE. Virulence. 2017; 8(4):453-459. PMID: 27470534 PMCID: PMC5477696
30. Ochiai T, Hamasaki T, Evans SR, Asakura K, Ohno Y. Group-sequential three-arm noninferiority clinical trial designs. J Biopharm Stat. 2017; 27(1):1-24. PMID: 26892481. PMCID: PMC4990829.
31. Asakura K, Hamasaki T, Evans SR. Interim evaluation of efficacy or futility in group-sequential trials with multiple co-primary endpoints. Biom J. 2017; 59(4):703-731. PMID: 27757980 PMCID: PMC6222168
32. Evans SR, Hujer AM, Jiang H, Hill CB, Hujer KM, Mediavilla JR, Manca C, Tran TT, Domitrovic TN, Higgins PG, Seifert H, Kreiswirth BN, Patel R, Jacobs MR, Chen L, Sampath R, Hall T, Marzan C, Fowler Jr VG, Chambers HF, Bonomo RA. Informing Antibiotic Treatment Decisions: Evaluating Rapid Molecular Diagnostics to Identify Susceptibility and Resistance to Carbapenems against Acinetobacter spp. in PRIMERS III. J Clin Microbiol. 2016; 55(1):134-144. PMID: 27795336 PMCID: PMC5228224
33. Evans SR, Follmann D. Using Outcomes to Analyze Patients Rather than Patients to Analyze Outcomes: A Step Toward Pragmatism in Benefit:risk Evaluation. Stat Biopharm Res. 2016; 8(4):386-393. PMID: 28435515 PMCID: PMC5394932
34. Evans SR, Pennello G, Pantoja-Galicia N, Jiang H, Hujer AM, Hujer KM, Manca C, Hill C, Jacobs MR, Chen L, Patel R, Kreiswirth BN, Bonomo RA. Benefit-risk Evaluation for Diagnostics: A Framework (BED-FRAME). Clin Infect Dis. 2016; 63(6):812-7. PMID: 27193750 PMCID: PMC4996133
35. Johnston SC, Amarenco P, Albers GW, Denison H, Easton JD, Evans SR, Held P, Jonasson J, Minematsu K, Molina CA, Wang Y, Wong L; SOCRATES Steering Committee and Investigators. Ticagrelor versus Aspirin in Acute Stroke or Transient Ischemic Attack. N Engl J Medicine. 2016; 375(1):35-43. PMID: 27160892
36. Pennello G, Pantoja-Galicia N, Evans SR. Comparing diagnostic tests on benefit-risk. J Biopharm Stat. 2016; 26(6):1083-1097. PMID: 27548805 PMCID: PMC5471848
37. Evans SR, Hujer AM, Jiang H, Hujer KM, Hall T, Marzan C, Jacobs MR, Sampath R, Ecker DJ, Manca C, Chavda K, Zhang P, Fernandez H, Chen L, Mediavilla JR, Hill CB, Perez F, Caliendo AM, Fowler Jr. VG, Chambers HF, Kreiswirth BN, and Bonomo RA;  Antibacterial Resistance Leadership Group. Rapid Molecular Diagnostics, Antibiotic Treatment Decisions, and Developing Approaches to Inform Empiric Therapy: PRIMERS I and II. Clin Infect Dis. 2016; 62(2):181-9. PMID: 26409063 PMCID: PMC4690483
38. Evans SR, Rubin D, Follmann D, Pennello G, Huskins WC, Powers JH, Schoenfeld D,  Chuang-Stein C, Cosgrove SE, Fowler Jr. VG, Lautenbach E, Chambers HF. Desirability of Outcome Ranking (DOOR) and Response Adjusted for Duration of Antibiotic Risk (RADAR). Clin Infect Dis. 2015; 61(5):800-6. PMID: 26113652 PMCID: PMC4542892
39. Uno H, Wittes J, Fu H, Solomon SD, Claggett B, Tian L, Cai T, Pfeffer MA, Evans SR, Wei LJ. Alternatives to hazard ratios for comparing efficacy or safety of therapies in noninferiority studies. Ann Intern Med. 2015; 163:127-134. PMID: 26054047 PMCID: PMC4510023.
40. Ando Y, Hamasaki T, Evans SR, Asakura K, Sugimoto T, Sozu T, Ohno Y. Sample size considerations in clinical trials when comparing two interventions using multiple co-primary binary relative risk contrasts. Stat Biopharm Res. 2015; 7(2):81-94. PMID: 26167243 PMCID: PMC4497828.
41. Hamasaki T, Asakura K, Evans SR, Sugimoto T, Suzo T. Group-sequential Strategies in Clinical Trials with Multiple Co-primary Outcomes. Stat Biopharm Res. 2015; 7(1):36-54. PMID: 25844122 PMCID: PMC4382106.
42. Asakura K, Hamasaki T, Sugimoto T, Hayashi K, Evans SR, Sozu T. Sample size determination in group-sequential clinical trials with two co-primary endpoints. Stat Med. 2014; 33(17):2897-913. PMID: 24676799 PMCID: PMC4082481
43. Chambers HF, Bartlett JG, Bonomo RA, Cosgrove S, Cross HR, Daum RS,  Evans SR, Knisely J, Kreiswirth BN, Lautenbach E, Mickley BS, Patel R, Pettigrew MM, Rodvold K, Spellberg B, Fowler Jr. VG. Antibacterial Resistance Leadership Group: Open for Business. Clin Infect Dis. 2014; 58(11):1571-6. PMID: 24610430 PMCID: PMC4017892
44. Sugimoto T, Sozu T, Hamasaki T, Evans SR. A Logrank Test-Based Method for Sizing Clinical Trials with Two Co-Primary Time-to-Event Endpoints. Biostatistics. 2013; 14(3):409-21. PMID: 23307913 PMCID: PMC4148615  
45. Hamasaki T, Evans SR. Noninferiority Clinical Trials: Issues in Design, Monitoring, Analyses, and Reporting. Igaku no Ayumi (Japanese) Translation: Int J Clin Exp Med. 2013; 244(13):1212-16.   
46. Hamasaki T, Sugimoto T, Evans SR, Sozu T. Sample Size Determination for Clinical Trials with Co-Primary Outcomes: Exponential Event-Times. Pharm Stat. 2013; 12(1):28-34. PMID: 23081932 PMCID: PMC3770150
47. Evans SR, Ellis RJ, Chen H, Yeh TM, Lee AJ, Schifitto G, Wu K, Bosch RJ, McArthur JC, Simpson DM, Clifford DB. Peripheral Neuropathy in HIV: Prevalence and Risk Factors. AIDS. 2011; 25(7):919-28. PMID: 21330902 PMCID: PMC3196556
48. Evans SR. Fundamentals of Clinical Trial Design. J Exp Stroke Transl Med. 2010; 3(1):19-27. PMID: 21533012 PMCID: PMC3083073
49. Evans SR. Clinical Trial Structures. J Exp Stroke Transl Med. 2010; 3(1):8-18. PMID: 21423788 PMCID: PMC3059315
50. Evans SR. Common Statistical Concerns in Clinical Trials. J Exp Stroke Transl Med. 2010; 3(1):1-7. PMID: 21423790 PMCID: PMC3059317
51. Evans SR. Estudos Clinicos de Nao-Inferioridade. Revista Brasileira de Medicina. 2010; 3(1):1-7.
52. Evans SR, Li L, Wei LJ. Data Monitoring in Clinical Trials Using Prediction. Drug Inf J. 2007; 41(6):733-742.
53. Evans SR, Fichtenbaum CJ, Aberg JA; A5087 Study Team. Comparison of Direct and Indirect Measurement of LDL-C in HIV Infected Individuals: ACTG 5087. HIV Clin Trials. 2007; 8(1):45-52. PMID: 17434848 PMCID: PMC2288650
54. Evans SR. When and How Can Endpoints Be Changed After Initiation of a Randomized Clinical Trial? PLoS Clin Trials. 2007; 2(4):e18. PMID: 17443237 PMCID: PMC1852589
55. Evans SR, Simpson DM, Kitch DW, King A, Clifford DB, Cohen BA, McArthur JC; Neurologic AIDS Research Consortium; AIDS Clinical Trials Group. A Randomized Trial Evaluating Prosaptide™ for HIV-Associated Sensory Neuropathies: Use of an Electronic Diary to Record Neuropathic Pain. PLoS One. 2007; 2(6):e551. PMID: 17653259 PMCID: PMC1919427
56. Evans SR, Wang R, Yeh TM, J Anderson, Haija R, McBratney-Owen PM, Peeples L,  Sinha S, Xanthakis V, Rajicic N, Zhang J. Evaluation of Distance Learning in an Introduction to Biostatistics Course. Statistical Education Research Journal. 2007; 6(2):59-77.
57. Evans SR, Li L. A Comparison of Goodness of Fit Tests for the Logistic GEE Model. Stat Med. 2005; 24(8):1245-61. PMID: 15580592
58. Evans SR, Hosmer DW. Goodness of Fit Tests for Mixed Effects Logistic Models Characterized by Clustering. Commun Stat Theory Methods. 2004; 33(5):1139-1155.
59. Evans SR, Hosmer DW. Goodness of Fit Tests for Logistic GEE Models: Simulation Results. Commun Stat Simul Comput. 2004; 33(1):247-258.
60. Evans SR, Krown SE, Testa MA, Cooley TP, Von Roenn JH. A Phase II Evaluation of Low-Dose Oral Etoposide for the Treatment of Relapsed or Progressive AIDS-Related Kaposi's Sarcoma: An ACTG Clinical Study. J Clin Oncol. 2002; 20(15):3236-41. PMID: 12149296