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Objective: Various statistical methods have been developed to estimate hazard ratios (HRs) from published Kaplan‐Meier (KM) curves for the purpose of performing meta‐analyses. The objective of this study was to determine the reliability, accuracy, and precision of four commonly used methods by Guyot, Williamson, Parmar, and Hoyle and Henley. Design Pivotal randomized controlled trials (RCTs) in oncology were identified from the pan‐Canadian Oncology Drug Review (pCODR) database (primary analysis) and the Food and Drug Administration's (FDA) drug approvals page (secondary analysis) between January 2012 and May 2016. Two reviewers independently reconstructed HRs using each method on KM curves extracted from each trial and compared them with reported HRs (gold standard). Bland‐Altman plots and summary statistics were calculated to assess accuracy and precision of these methods. Interrater reliability was assessed using intraclass correlation coefficient (ICC). These four methods were also applied to KM curves of different structures (ie, flat versus steep curves). Results: A total of 118 KM curves (55 RCTs) and 77 KM curves (46 RCTs) were extracted from pCODR and FDA, respectively. In the primary analysis, the Guyot method was the most accurate with the lowest mean error (0.0094; 95% CI, −0.0012‐0.020). All four methods had excellent interrater reliability. The Guyot method showed the smallest bias and greatest precision on the Bland‐Altman plots. The Guyot method was consistently superior in both the secondary and all sensitivity analyses. Conclusion: In the absence of reported HRs, we recommend that researchers consider the Guyot method to reconstruct HRs from KM curves when performing aggregate data meta‐analyses. [ABSTRACT FROM AUTHOR]

Background older patients are commonly believed to derive less benefit from cancer drugs, even if they fulfil clinical trial eligibility [Talarico et al. (2004, J Clin Oncol, 22(22):4626–31)]. We aim to examine if novel oncology drugs provide differential age-based treatment outcomes for patients on clinical trials. Methods a systematic review of randomised control trials (RCTs) cited for clinical efficacy evidence in novel oncology drug approvals by the Food and Drug Administration, European Medicines Agency and Health Canada between 2006 and 2017 was conducted. Studies reporting age-based subgroup analyses for overall or progression-free survival (OS/PFS) were included. Hazard ratios (HRs) and confidence intervals (CIs) for age-based subgroups were extracted. Meta-analyses with random effects were conducted, examining patient subgroups <65 and ≥65 years separately and pooled HRs of studies primary endpoints (OS or PFS) compared to examine if differences existed between age-based subgroups. Sensitivity analyses were conducted for cancer type, primary endpoint and systemic treatment. Results one-hundred-two RCTs, including 65,122 patients, met the inclusion criteria. One study reported age-based toxicity and none reported age-based quality of life (QOL) results. Pooled HRs [95% CIs] for patients <65 and ≥65 years were 0.61 [0.57–0.65] and 0.65 [0.61–0.70], respectively, with no difference between them (P = 0.14). Sensitivity analyses revealed similar results. Conclusion our results suggest that older and young patients, who fulfil clinical trial eligibility, may derive similar relative survival benefits from novel oncology drugs. There is, however, a need to report age-based toxicity and QOL results to support patient discussions regarding the balance of treatment benefit and harm, to encourage informed decision-making. [ABSTRACT FROM AUTHOR]