Abstract
Survival analyses are a powerful statistical tool used to analyse data when the outcome of interest involves the time until an event. There is an array of models fit for this goal; however, there are subtle differences in assumptions, as well as a number of pitfalls, that can lead to biased results if researchers are unaware of the subtleties. As larger amounts of data become available, and more survival analyses are published every year, it is important that healthcare professionals understand how to evaluate these models and apply them into their practice. Therefore, the purpose of this study was to present an overview of survival analyses, including required assumptions and important pitfalls, as well as examples of their use within orthopaedic surgery.
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References
Argenson J-N, Boisgard S, Parratte S, Descamps S, Bercovy M, Bonnevialle P et al (2013) Survival analysis of total knee arthroplasty at a minimum 10 years’ follow-up: a multicenter French nationwide study including 846 cases. Orthop Traumatol-Sur 99:385–390
Bewick V, Cheek L, Ball J (2004) Statistics review 12: survival analysis. Crit Care. https://doi.org/10.1186/cc2955
Bland JM, Altman DG (2004) The logrank test. Br Med J 328:1073
Bouliotis G, Billingham L (2011) Crossing survival curves: alternatives to the log-rank test. Trials 12:1–1
Clark TG, Bradburn MJ, Love SB, Altman DG (2003) Survival analysis part I: basic concepts and first analyses. Br J Cancer 89:232–238
Cox DR (1972) Regression models and life-tables. J R Stat Soc B 34:187–202
Crowson CS, Larson DR, Devick KL, Atkinson EJ, Lundgreen CS, Lewallen DG et al (2021) Living with survival analysis in orthopedics. J Arthroplasty 36:3358–3361
Crowther MJ, Lambert PC (2014) A general framework for parametric survival analysis. Stat Med 33:5280–5297
DeFrancesco CJ, Striano BM, Bram JT, Baldwin KD, Ganley TJ (2020) An in-depth analysis of graft rupture and contralateral anterior cruciate ligament rupture rates after pediatric anterior cruciate ligament reconstruction. Am J Sports Med 48:2395–2400
Goel MK, Khanna P, Kishore J (2010) Understanding survival analysis: Kaplan–Meier estimate. Int J Ayurveda Res. https://doi.org/10.4103/0974-7788.76794
Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J Am Stat Assoc 53:457–481
Katz JN, Wright EA, Wright J, Malchau H, Mahomed NN, Stedman M et al (2012) Twelve-year risk of revision after primary total hip replacement in the US Medicare population. J Bone Joint Surg Am 94:1825
Kleinbaum DG, Klein M (2012) Survival analysis: a self-learning text, vol 3. Springer, New York, pp 2–350
Kuitunen I, Ponkilainen VT, Uimonen MM, Eskelinen A, Reito A (2021) Testing the proportional hazards assumption in cox regression and dealing with possible non-proportionality in total joint arthroplasty research: methodological perspectives and review. BMC Musculoskelet Disord. https://doi.org/10.1186/s12891-021-04379-2
Larson DR, Crowson CS, Devick KL, Lewallen DG, Berry DJ, Kremers HM (2021) Immortal time bias in the analysis of time-to-event data in orthopedics. J Arthroplasty 36:3372–3377
Lévesque LE, Hanley JA, Kezouh A, Suissa S (2010) Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. Br Med J 340:5087
Lim HJ, Zhang X (2011) Additive and multiplicative hazards modeling for recurrent event data analysis. BMC Med Res Methodol. https://doi.org/10.1186/1471-2288-11-101
Mantel N (1966) Evaluation of survival data and two new rank order statistics arising in its consideration. Cancer Chemother Rep 50:163–170
Maradit Kremers H, Devick KL, Larson DR, Lewallen DG, Berry DJ, Crowson CS (2021) Competing risk analysis: what does it mean and when do we need it in orthopedics research? J Arthroplasty 36:3362–3366
Moore DF (2016) Applied survival analysis using R, vol 473. Springer, New York, pp 1–10
Nepple JJ, Parilla FW, Ince DC, Freiman S, Clohisy JC (2022) Does femoral osteoplasty improve long-term clinical outcomes and survivorship of hip arthroscopy? A 15-year minimum follow-up study. Am J Sports Med 50:3586–3592
Owens BD, Campbell SE, Cameron KL (2013) Risk factors for posterior shoulder instability in young athletes. Am J Sports Med 41:2645–2649
Owens BD, Campbell SE, Cameron KL (2014) Risk factors for anterior glenohumeral instability. Am J Sports Med 42:2591–2596
Pallis M, Svoboda SJ, Cameron KL, Owens BD (2012) Survival comparison of allograft and autograft anterior cruciate ligament reconstruction at the United States Military Academy. Am J Sports Med 40:1242–1246
Rich JT, Neely JG, Paniello RC, Voelker CC, Nussenbaum B, Wang EW (2010) A practical guide to understanding Kaplan-Meier curves. Otolaryngol Head Neck Surg 143:331–336
Sonnery-Cottet B, Saithna A, Blakeney WG, Ouanezar H, Borade A, Daggett M et al (2018) Anterolateral ligament reconstruction protects the repaired medial meniscus: a comparative study of 383 anterior cruciate ligament reconstructions from the SANTI study group with a minimum follow-up of 2 years. Am J Sports Med 46:1819–1826
Suissa S (2008) Immortal time bias in pharmacoepidemiology. Am J Epidemiol 167:492–499
Varady NH, Abraham PF, Kucharik MP, Freccero DM, Smith EL, Martin SD (2022) Comparing the risk of osteonecrosis of the femoral head following intra-articular corticosteroid and hyaluronic acid injections. J Bone Joint Surg Am 10:2106
Varady NH, Pareek A, Eckhardt CM, Williams RJ, Madjarova SJ, Ollivier M et al (2022) Multivariable regression: understanding one of medicine’s most fundamental statistical tools. Knee Surg Sports Traumatol Arthrosc. https://doi.org/10.1007/s00167-022-07215-9
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Pruneski, J.A., Varady, N.H., Pareek, A. et al. Survival analyses and their applications in orthopaedics. Knee Surg Sports Traumatol Arthrosc 31, 2053–2059 (2023). https://doi.org/10.1007/s00167-023-07371-6
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DOI: https://doi.org/10.1007/s00167-023-07371-6