Editorial

Reporting Standards for Clinical and Translational Research

Fengyu Zhang and Claude Hughes

Transparency in reporting the results of clinical and preclinical research is critical for unbiased publications. Funding agencies, publishers, and regulators have the responsibility to advocate and implement reporting standards for rigorous design. While individual study protocols may have included these standards, the items reported in the respective publications have often been inconsistent or lack transparency. This editorial intends to provide some specific guidelines for reporting results of clinical research with standards required for a rigorous study design. We recommend that reporting clinical research should include sufficient information on study design and analysis plan that contains data processing, quality assurance, and appropriate methods used for rigorous statistical analysis or modeling. Any discrepancy between publications and original study design should be disclosed and discussed. Additionally, recent advances in the analysis of outcome with repeated measurements and statistical modeling should be employed to obtain an unbiased estimates. Finally, we briefly discuss some issues reporting real-world evidence in clinical research.

Copyright 2019 by Global Clinical and Translational Research.

How to cite this article:

Zhang F and Hughes C. Reporting Standards for Clinical and Translational Research. Glob Clin Transl Res. 2019; 1(2): 69-73. DOI:10.36316/gcatr.01.0010.

References

1.       Dwan K, Altman DG, Clarke M, Gamble C, Higgins JP, Sterne JA, et al. Evidence for the selective reporting of analyses and discrepancies in clinical trials: a systematic review of cohort studies of clinical trials. PLoS Med. 2014;11(6):e1001666.

2.       Al-Marzouki S, Roberts I, Marshall T, Evans S. The effect of scientific misconduct on the results of clinical trials: a Delphi survey. Contemp Clin Trials. 2005;26(3):331-7.

3.       Rankin J, Ross A, Baker J, O'Brien M, Scheckel C, Vassar M. Selective outcome reporting in obesity clinical trials: a cross-sectional review. Clin Obes. 2017;7(4):245-54.

4.       Bourgeois FT, Murthy S, Mandl KD. Outcome reporting among drug trials registered in ClinicalTrials.gov. Ann Intern Med. 2010;153(3):158-66.

5.       Landis SC, Amara SG, Asadullah K, Austin CP, Blumenstein R, Bradley EW, et al. A call for transparent reporting to optimize the predictive value of preclinical research. Nature. 2012; 490(7419):187-91.

6.       Journals unite for reproducibility. Nature. 2014;515(7525):7.

7.       McNutt M. Journals unite for reproducibility. Science. 2014;346(6210):679.

8.       Leek JT, Peng RD. Statistics: P values are just the tip of the iceberg. Nature. 2015;520(7549):612.

9.       MacKinnon DP, Lockwood CM, Brown CH, Wang W, Hoffman JM. The intermediate endpoint effect in logistic and probit regression. Clin Trials. 2007;4(5):499-513.

10.    Coxe S, West SG, Aiken LS. The analysis of count data: a gentle introduction to poisson regression and its alternatives. J Pers Assess. 2009;91(2):121-36.

11.    Lieberman JA, Stroup TS, McEvoy JP, Swartz MS, Rosenheck RA, Perkins DO, et al. Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. N Engl J Med. 2005; 353(12):1209-23.

12.    Austin PC. A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications. Int Stat Rev. 2017; 85(2): 185-203.

13.    Ioannidis JP. Why most published research findings are false. PLoS Med. 2005;2(8):e124.

14.    Nuzzo R. Scientific method: statistical errors. Nature. 2014; 506(7487):150-2.

15.    Ioannidis JPA. The Proposal to Lower P Value Thresholds to .005. JAMA. 2018;319(14):1429-30.

16.    Hougaard P. Frailty models for survival data. Lifetime Data Anal. 1995;1(3):255-73.

17.    Short S, Zhang F. Use of maternal health services in rural China. Population Studies. 2004;58(1):3-19.

18.    Zhang F, Tsui A, Suchindran C. The determinants of contraceptive discontinuation in Northern India: A multilevel analysis of calander data. . The MEASURE Evaluation Working Paper WP-99-15 1999.

19.    Wu RR, Zhang FY, Gao KM, Ou JJ, Shao P, Jin H, et al. Metformin treatment of antipsychotic-induced dyslipidemia: an analysis of two randomized, placebo-controlled trials. Mol Psychiatry. 2016;21(11):1537-44.

20.    Csernansky JG, Mahmoud R, Brenner R, Risperidone USASG. A comparison of risperidone and haloperidol for the prevention of relapse in patients with schizophrenia. N Engl J Med. 2002;346(1):16-22.

21.    Boudreau JE, Giglio F, Gooley TA, Stevenson PA, Le Luduec JB, Shaffer BC, et al. KIR3DL1/ HL A-B Subtypes Govern Acute Myelogenous Leukemia Relapse After Hematopoietic Cell Transplantation. J Clin Oncol. 2017;35(20):2268-78.

22.    Apud JA, Zhang F, Decot H, Bigos KL, Weinberger DR. Genetic variation in KCNH2 associated with expression in the brain of a unique hERG isoform modulates treatment response in patients with schizophrenia. Am J Psychiatry. 2012; 169 (7): 725-34.

23.    Jenkins A, Apud JA, Zhang F, Decot H, Weinberger DR, Law AJ. Identification of candidate single-nucleotide polymorphisms in NRXN1 related to antipsychotic treatment response in patients with schizophrenia. Neuropsychopharmacology. 2014;39(9):2170-8.

24.    Molnar FJ, Hutton B, Fergusson D. Does analysis using "last observation carried forward" introduce bias in dementia research? CMAJ. 2008;179(8):751-3.

25.    Panel NRCU. The Prevention and Treatment of Missing Data in Clinical Trials. Washington (DC)2010.

26.    Swift B, Jain L, White C, Chandrasekaran V, Bhandari A, Hughes DA, et al. Innovation at the Intersection of Clinical Trials and Real-World Data Science to Advance Patient Care. Clin Transl Sci. 2018;11(5):450-60.

27.    Shader RI. Pharmacovigilance and Some Thoughts About What We Eat. Clin Ther. 2018;40(12):1957-61.

28.   Jarow JP, LaVange L, Woodcock J. Multidimensional Evidence Generation and FDA Regulatory Decision Making: Defining and Using "Real-World" Data. JAMA. 2017;318(8):703-4.