Interpretation of effect measures in clinical research: A practical guide for the clinician
Main Article Content
Keywords
Evidence-Based Medicine, Data Interpretation, Statistical, Clinical Decision-Making, Clinical Research Protocols
Abstract
Abstract
Modern medical practice faces an ever-growing volume of information that demands accurate statistical interpretation to guide clinical decision-making. Effect measures are essential tools for quantifying the true magnitude of an intervention and assessing its clinical impact. However, limited understanding of these measures among healthcare professionals often hinders the effective translation of evidence into everyday practice. This article’s objective is to provide a clear and didactic overview of the principal effect measures used in clinical research, emphasizing their relevance to evidence-based medicine. Key concepts such as the p-value, confidence intervals, relative risk, absolute risk reduction, and number needed to treat are summarized. The p-value reflects statistical significance, but it does not convey the magnitude or clinical importance of an effect. Confidence intervals, on the other hand, offer information about the precision and direction of the estimated effect. Relative risk facilitates the comparison of probabilities between groups, while absolute risk reduction and number needed to treat provide more tangible measures for clinical application. The adequate interpretation of these concepts is a cornerstone of evidence-based medicine, it enables clinicians to critically appraise research findings, and make patient-centered decisions, thereby narrowing the gap between scientific evidence and clinical practice.
References
1. Karunarathna I, Gunasena P, Aluthge P, et al. From Data to Decisions: The Role of Statistics in Healthcare. Montfort Hosp. 2024;1-6. doi:10.13140/RG.2.2.36334.11843
2. Kang H. How to understand and conduct evidence-based medicine. Korean J Anesthesiol. 2016;69(5):435-45. doi: 10.4097/kjae.2016.69.5.435
3. Davis SL, Johnson AH, Lynch T, et al. Inclusion of effect size measures and clinical relevance in research papers. Nurs Res. 2021;70(3):222-30. doi:10.1097/NNR.0000000000000494
4. Higgins JP, Li T, Deeks JJ. Chapter 6: Choosing effect measures and computing estimates of effect. In: Cochrane Handbook for Systematic Reviews of Interventions. Disponible en: https://www.cochrane.org/authors/handbooks-and-manuals/handbook/current/chapter-06
5. Wouk K, Kenny K, Chetwynd E. About Research: Clinical Versus Statistical Significance. J Hum Lact. 2025 Mar;41(2):181-4. doi: 10.1177/08903344251320587
6. Lozada-Martínez ID, Acevedo-Aguilar LM, Mass-Hernández LM, et al. Practical guide for the use of medical evidence in scientific publication: Recommendations for the medical student: Narrative review. Ann Med Surg. 2021;71:102932. doi: 10.1016/j.amsu.2021.102932
7. Baethge C, Goldbeck-Wood S, Mertens S. SANRA-a scale for the quality assessment of narrative review articles. Res Integr Peer Rev. 2019;4:5. doi: 10.1186/s41073-019-0064-8
8. Illowsky B, Dean S, Illowsky B, et al. Contingency Tables.On: Statistics. OpenStax; 2020. Disponible en: https://openstax.org/books/statistics/pages/3-4-contingency-tables
9. Shreffler J, Huecker MR. Hypothesis Testing, P Values, Confidence Intervals, and Significance. En: StatPearls. Treasure Island (FL): StatPearls Publishing; 2025. Disponible en: http://www.ncbi.nlm.nih.gov/books/NBK557421/
10. White SE. Probabilidad y temas relacionados para hacer inferencias sobre los datos. En: Bioestadística Básica y Clínica. 5ta Ed. McGraw-Hill Medical; 2025.
11. Bonovas S, Piovani D, Bonovas S, et al. On p-Values and Statistical Significance. J Clin Med. 2023;12(3). doi: 10.3390/jcm12030900
12. AbdulRaheem Y. Statistical Significance versus Clinical Relevance: Key Considerations in Interpretation Medical Research Data. Indian J Community Med Off Publ Indian Assoc Prev Soc Med. 2024;49(6):791-5. doi: 10.4103/ijcm.ijcm_601_23
13. Sharma H. Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi J Anaesth. 2021;15(4):431-4. doi: 10.4103/sja.sja_158_21
14. Chén OY, Bodelet JS, Saraiva RG, et al. The roles, challenges, and merits of the p value. Patterns. 2023;4(12):100878. doi: 10.1016/j.patter.2023.100878
15. Swedberg K, Kjekshus J. Effects of enalapril on mortality in severe congestive heart failure: results of the Cooperative North Scandinavian Enalapril Survival Study (CONSENSUS). Am J Cardiol. 1988;62(2):60A-66A.
16. Heidenreich PA, Bozkurt B, Aguilar D, et al.; ACC/AHA Joint Committee Members. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022;145(18):e895-1032. doi: 10.1161/CIR.0000000000001063
17. George A, Stead TS, Ganti L. What’s the Risk: Differentiating Risk Ratios, Odds Ratios, and Hazard Ratios? Cureus. 2020;12(8):e10047. doi: 10.7759/cureus.10047
18. Vargas F. Concepto de causalidad en Medicina. En: Epidemiología clínica. 3era ed. McGraw-Hill Medical; 2025. Disponible en: https://accessmedicina.mhmedical.com/content.aspx?bookId=1442§ionId=101159243
19. Sharma SK, Mudgal SK, Chaturvedi J. Expression and interpretation of relative risk and odds ratio in biomedical research studies. Indian J Community Health. 2020;32(2):344-7. doi: 10.47203/ijch.2020.v32i02.008
20. Ranganathan P, Aggarwal R, Pramesh CS. Common pitfalls in statistical analysis: Odds versus risk. Perspect Clin Res. 2015;6(4):222. doi:10.4103/2229-3485.167092
21. Doi SA, Furuya-Kanamori L, Xu C, et al. Controversy and Debate: Questionable utility of the relative risk in clinical research. J Clin Epidemiol. 2022;142:271-9. doi: 10.1016/j.jclinepi.2020.08.019
22. Monaghan TF, Rahman SN, Agudelo CW, et al. Foundational Statistical Principles in Medical Research: A Tutorial on Odds Ratios, Relative Risk, Absolute Risk, and Number Needed to Treat. Int J Environ Res Public Health. 2021;18(11):5669. doi: 10.3390/ijerph18115669
23. Irwig L, Irwig J, Trevena L, et al. Relative risk, relative and absolute risk reduction, number needed to treat and confidence intervals. On: Smart Health Choices: Making Sense of Health Advice. Hammersmith Press; 2008.
24. Zavala S, Stout JE. Understanding and Communicating Risk: Assessing Both Relative and Absolute Risk Is Absolutely Necessary. JID Innov. 2022;2(2):100097. doi: 10.1016/j.xjidi.2022.100097
25. Andersen LW. Absolute vs. relative effects—implications for subgroup analyses. Trials. 2021;22:50. doi: 10.1186/s13063-020-05005-7
26. Lovaldi ML. Relative risk and odds ratio: basic concepts. Rev Argent Cir. 2023;115(4):310-5. doi: 10.25132/raac.v115.n4.cymmli
27. Park SH, Han K. How to Clearly and Accurately Report Odds Ratio and Hazard Ratio in Diagnostic Research Studies? - Korean J Radiol. 2022;23(8):777-84. doi: 10.3348/kjr.2022.0249
28. Andrade C. How to Understand the 95% Confidence Interval Around the Relative Risk, Odds Ratio, and Hazard Ratio: As Simple as It Gets. J Clin Psychiatry. 2023;84(3):23f14933. doi: 10.4088/JCP.23f14933
29. Gupta L, Chaudhary K, Bharti D. Confidence interval reporting in randomised controlled trials: A critical analysis of IJA publications. Indian J Anaesth. 2025;69(10):1069. doi: 10.4103/ija.ija_811_25
30. Sharma PK, Yadav M. Confidence Interval: Advantages, Disadvantages and the Dilemma of Interpretation. Rev Recent Clin Trials. 2024;19(1):76-80. doi: 10.2174/0115748871266250231120043345
31. Vancak V, Goldberg Y, et al. Guidelines to understand and compute the number needed to treat. Evid Based Ment Health. 2021;24(4):131-6. doi: 10.1136/ebmental-2020-300232
32. Davis MP, Vanenkevort E. Understanding the Number Needed to Treat. J Pain Symptom Manage. 2024;68(3): e190-3. doi: 10.1016/j.jpainsymman.2024.06.002
33. Jassir Acosta MP, Gómez-Restrepo C. Número necesario a tratar y número necesario para producir daño: su importancia. Univ. Med. 2021;62(2). doi: 10.11144 Javeriana.umed62-2.nnnt
34. D’Arrigo G, Gori M, Pitino A, et al. Measures of frequency and effect in clinical research. Int Urol Nephrol. 2023;55,3147-52 doi: 10.1007/s11255-023-03626-w
35. Jiroutek MR, Turner JR. Relative vs absolute risk and odds: Understanding the difference. J Clin Hypertens Greenwich Conn. 2019;21(6):859-61. doi: 10.1111/jch.13548
36. Willigenburg NW, Poolman RW. The difference between statistical significance and clinical relevance. The case of minimal important change, non-inferiority trials, and smallest worthwhile effect. Injury. 2023; 54 Suppl 5:110764.
37. Rendón-Macías ME, García H, Villasís-Keever MA. Medidas de riesgo, asociación e impacto en los estudios de investigación clínica. Cómo interpretarlas para su aplicación en la atención médica. Revista Alergia México; 2021:68(1):65-75. doi: 10.29262/ram.v68i1.886
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