IPDfromKM: reconstruct individual patient data from published Kaplan-Meier survival curvesNa Liu, Yanhong Zhou, J. Jack Lee|BMC Medical Research Methodology|2021 BACKGROUND: When applying secondary analysis on published survival data, it is critical to obtain each patient's raw data, because the individual patient data (IPD) approach has been considered as the gold standard of data analysis. However, researchers often lack access to IPD. We aim to propose a straightforward and robust approach to obtain IPD from published survival curves with a user-friendly software platform. RESULTS: Improving upon existing methods, we propose an easy-to-use, two-stage approach to reconstruct IPD from published Kaplan-Meier (K-M) curves. Stage 1 extracts raw data coordinates and Stage 2 reconstructs IPD using the proposed method. To facilitate the use of the proposed method, we developed the R package IPDfromKM and an accompanying web-based Shiny application. Both the R package and Shiny application have an "all-in-one" feature such that users can use them to extract raw data coordinates from published K-M curves, reconstruct IPD from the extracted data coordinates, visualize the reconstructed IPD, assess the accuracy of the reconstruction, and perform secondary analysis on the basis of the reconstructed IPD. We illustrate the use of the R package and the Shiny application with K-M curves from published studies. Extensive simulations and real-world data applications demonstrate that the proposed method has high accuracy and great reliability in estimating the number of events, number of patients at risk, survival probabilities, median survival times, and hazard ratios. CONCLUSIONS: IPDfromKM has great flexibility and accuracy to reconstruct IPD from published K-M curves with different shapes. We believe that the R package and the Shiny application will greatly facilitate the potential use of quality IPD and advance the use of secondary data to facilitate informed decision making in medical research.
Oncogene-specific differences in tumor mutational burden, PD-L1 expression, and outcomes from immunotherapy in non-small cell lung cancerBackground Non-small cell lung cancer (NSCLC) patients bearing targetable oncogene alterations typically derive limited benefit from immune checkpoint blockade (ICB), which has been attributed to low tumor mutation burden (TMB) and/or PD-L1 levels. We investigated oncogene-specific differences in these markers and clinical outcome. Methods Three cohorts of NSCLC patients with oncogene alterations (n=4189 total) were analyzed. Two clinical cohorts of advanced NSCLC patients treated with ICB monotherapy [MD Anderson (MDACC; n=172) and Flatiron Health-Foundation Medicine Clinico-Genomic Database (CGDB; n=894 patients)] were analyzed for clinical outcome. The FMI biomarker cohort (n=4017) was used to assess the association of oncogene alterations with TMB and PD-L1 expression. Results High PD-L1 expression (PD-L1 ≥50%) rate was 19%–20% in classic EGFR , EGFR exon 20 and HER2 -mutant tumors, and 34%–55% in tumors with ALK , BRAF V600E, ROS1 , RET , or MET alterations. Compared with KRAS- mutant tumors, BRAF non-V600E group had higher TMB (9.6 vs KRAS 7.8 mutations/Mb, p=0.003), while all other oncogene groups had lower TMB (p<0.001). In the two clinical cohorts treated with ICB, molecular groups with EGFR , HER2 , ALK , ROS1 , RET , or MET alterations had short progression-free survival (PFS; 1.8–3.7 months), while BRAF V600E group was associated with greater clinical benefit from ICB (CGDB cohort: PFS 9.8 months vs KRAS 3.7 months, HR 0.66, p=0.099; MDACC cohort: response rate 62% vs KRAS 24%; PFS 7.4 vs KRAS 2.8 months, HR 0.36, p=0.026). KRAS G12C and non-G12C subgroups had similar clinical benefit from ICB in both cohorts. In a multivariable analysis, BRAF V600E mutation (HR 0.58, p=0.041), PD-L1 expression (HR 0.57, p=0.022), and high TMB (HR 0.66, p<0.001) were associated with longer PFS. Conclusions High TMB and PD-L1 expression are predictive for benefit from ICB treatment in oncogene-driven NSCLCs. NSCLC harboring BRAF mutations demonstrated superior benefit from ICB that may be attributed to higher TMB and higher PD-L1 expression in these tumors. Meanwhile EGFR and HER2 mutations and ALK , ROS1 , RET , and MET fusions define NSCLC subsets with minimal benefit from ICB despite high PD-L1 expression in NSCLC harboring oncogene fusions. These findings indicate a TMB/PD-L1-independent impact on sensitivity to ICB for certain oncogene alterations.