Supplementary Online Content Goss GD, Felip E, Cobo M, et al. Association of ERBB mutations with clinical outcomes of afatinib- or erlotinib-treated patients with lung squamous cell carcinoma: secondary analysis of the LUX-Lung 8 randomized clinical trial. JAMA Oncol. Published online June 14, 2018. doi:10.1001/jamaoncol.2018.0775 eAppendix. Methods eReferences. eTable 1. Baseline Clinical Characteristics eTable 2. All Genetic Aberrations Detected in the TGA Cohort eTable 3. Relationship Between EGFR Expression Status and PFS and OS eFigure 1. Comparison of Clinical Outcomes in the TGA Cohort and Overall LUX-Lung 8 (Intent-to-Treat) Population eFigure 2. Relationship Between the Most Frequent Tumor Genetic Aberrations and (A) PFS and (B) OS in the LUX-Lung 8 TGA Cohort eFigure 3. (A) Details of ErbB Family Mutations; (B) Location of HER2 Mutations eFigure 4. Standardized Effect Plot for PFS (Left) and OS (Right) This supplementary material has been provided by the authors to give readers additional information about their work. © 2018 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/26/2021 eAppendix. Methods Selection of samples for sequencing Selection of patients was performed in the following order: 1. From the first 176 patients investigated in the LUX-Lung 8 interim analysis (based on independent radiological review [IRR]), samples from patients that were in the upper and lower quartiles of maximum tumor shrinkage or had PFS > 6 months were selected. Upper and lower quartiles of maximum tumor shrinkage were investigated by an independent statistician. 2. From the data available for primary PFS analyses (based on IRR), all patients with a PFS > 2 months (censored or non-censored) were selected. For patients with a PFS ≤ 2 months and with progressive disease as the best overall response, 120 patients , i.e. 60 patients per treatment arm that were non-censored for PFS, were selected randomly. As the enrichment process may lead to a bias in the statistical analysis, we always carefully interpreted HRs (afatinib vs erlotinib) in any given biomarker subgroup relative to the hazard ratio in the TGA subset and not the HR in the overall LUX-Lung 8 population.. Tumor samples from patients in China were not available for sequencing due to legal requirements, and had to be excluded from this analysis. Statistical analysis The predictive potential of a binary biomarker variable B (alteration present/absent) was investigated using a Cox’s proportional hazard model. The hazard function of the ith patient is: ∙ ∙ ∙ ∙ ∙, where t is the time point, is the baseline hazard function stratified by race (Eastern Asian vs Non-eastern Asian), and is the treatment effect. Ties were handled using the Breslow method. The P-value for the biomarker-by- treatment interaction was reported. Further, for each biomarker-defined subgroup, HRs (afatinib vs erlotinib) and their 95% Wald CIs were provided based on the hazard function: ∙ ∙. Due to the small size of the biomarker-defined subgroups, the subgroup models were not stratified by race. Kaplan-Meier curves for the two treatments were constructed for the biomarker-defined subgroups. The median of the time-to-event endpoint and its 95% CI were estimated using a log-log transformation. All biomarker variables were analyzed separately. Multivariate models were not considered. Only patients without missing biomarker information were considered in this analysis. Unadjusted P -values are reported throughout the main manuscript. Adjustments for multiple comparisons were performed using standardized effect plots (see Supplementary Results). The significance level was defined as α = .05. Analyses were performed using SAS version 9.2 or higher and R version 3.3.2 or higher. Sample size considerations This was a retrospective and exploratory study, and no formal sample size calculation was performed. In particular, the study was not powered to detect a significant predictive biomarker effect, which typically requires large sample sizes or substantial effects.1 Results Standardized effect plots were produced to investigate if the relative treatment benefit (afatinib vs erlotinib) observed in a subgroup was different to the relative treatment benefit observed in the TGA.2 The standardized effect of a subgroup S was defined as: log log © 2018 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/26/2021 with the hazard ratio in the subgroup, the hazard ratio in the TGA, and the standard deviation of . A standardized effect <0 implied that the relative treatment benefit was more pronounced in the subgroup compared to the relative treatment benefit in the TGA. P-values for the standardized effects were obtained using a permutation approach (i.e. by randomly permuting the clinical endpoint within each treatment arm R = 2000 times and estimating the standardized effects on these permuted data). In addition, to correct for multiple testing, an adjusted 95% CI and an adjusted P-value for the HER2 mutation-positive subgroup was computed. Supplementary eFigure 4 displays the results. Unadjusted P-values for the HER2 mutation-positive subgroup were <.05 for PFS and OS. After correction for multiple comparisons, the adjusted P-values for this subgroup were .067 (PFS) and .052 (OS). eReferences 1. Schmoor C, Sauerbrei W, Schumacher M. Sample size considerations for the evaluation of prognostic factors in survival analysis. Stat Med. 2000;19(4):441-452. 2. Dane, A. Standardised effect plots. Oral presentation presented at: 2016 PSI Conference 'Promoting Statistical Insight and Collaboration in Drug Development'; May 22 – 25, 2016; Berlin. © 2018 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/26/2021 eTable 1. Baseline Clinical Characteristics Characteristic Overall TGA subset IHC analysis population (n = 245) subset (N = 795) (n = 345) Mean age (standard deviation) 64.1 (8.7) 64.4 (8.4) 63.9 (9.1) Gender (%) Female 16.2 11.8 16.8 Male 83.8 88.2 83.2 Ethnic origin (%) Non-eastern Asian 78.4 80.4 71.3 Eastern Asian 21.6 19.6 28.7 ECOG PS (%) 0 32.7 35.5 31.6 1 66.8 63.7 67.8 2 0.5 0.8 0.6 Smoking history (%) Never smoker 5.5 5.3 6.1 Light ex-smokera 2.9 3.3 1.7 Current or other ex-smoker 91.6 91.4 92.2 Tumor histology (%)b Squamous 96.0 96.7 95.7 Mixed 4.0 3.3 4.3 Best response to first-line Chemotherapy (%) CR/PR 46.7 45.3 47.2 SD 41.3 43.7 40.9 PD 0.9 0.0 1.2 Unknown 11.2 11.0 10.7 Abbreviations: CR, complete response; ECOG PS, Eastern Cooperative Oncology Group performance status; IHC, immunohistochemistry; PD, progressive disease; PR, partial response; SD, stable disease; TGA, tumor genetic analysis. a<15 pack-years and stopped >1 year before diagnosis. b4 patients in the erlotinib group in the overall population and IHC subset had undifferentiated tumor histology but were considered to be squamous by the treating investigator. © 2018 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/26/2021 eTable 2. All Genetic Aberrations Detected in the TGA Cohort Gene At least one SV CNA REAR n % n % n % Total 245 100 245 100 245 100 ABL1 7 2.9 – – – – AKT1 4 1.6 4 1.6 – – AKT2 1 0.4 9 3.7 – – AKT3 7 2.9 2 0.8 – – ALK 24 9.8 – – 2 0.8 ALOX12B 5 2 – – – – APC 14 5.7 1 0.4 1 0.4 APCDD1 10 4.1 2 0.8 – – AR 21 8.6 – – – – ARAF 3 1.2 – – – – ARFRP1 2 0.8 4 1.6 – – ARID1A 27 11 – – 1 0.4 ARID2 13 5.3 2 0.8 – – ASXL1 10 4.1 9 3.7 – – ATM 30 12.2 – – – – ATR 24 9.8 17 6.9 1 0.4 ATRX 9 3.7 – – – – AURKA 5 2 1 0.4 – – AURKB 1 0.4 2 0.8 – – AXL 15 6.1 3 1.2 1 0.4 BACH1 10 4.1 – – 1 0.4 BAP1 5 2 1 0.4 – – BARD1 15 6.1 – – – – BCL2 2 0.8 1 0.4 – – BCL2L2 1 0.4 6 2.4 – – BCL6 10 4.1 75 30.6 – – BCOR 14 5.7 – – – – BCORL1 10 4.1 – – – – BCR – – – – 1 0.4 BLM 13 5.3 – – – – BRAF 7 2.9 – – – – BRCA1 14 5.7 – – – – BRCA2 34 13.9 – – – – BRIP1 24 9.8 1 0.4 – – © 2018 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/26/2021 BTK 2 0.8 – – – – C11orf30 9 3.7 – – – – C17orf39 3 1.2 1 0.4 – – CARD11 16 6.5 2 0.8 – – CASP8 6 2.4 4 1.6 – – CBFB – – 1 0.4 – – CBL 13 5.3 – – – – CCND1 2 0.8 32 13.1 – – CCND2 4 1.6 14 5.7 – – CCND3 3 1.2 3 1.2 – – CCNE1 3 1.2 14 5.7 – – CD79A 1 0.4 2 0.8 – – CD79B 3 1.2 1 0.4 – – CDC73 5 2 2 0.8 – – CDH1 9 3.7 – – 1 0.4 CDK12 12 4.9 5 2 1 0.4 CDK4 2 0.8 4 1.6 – – CDK6 1 0.4 9 3.7 – – CDK8 2 0.8 – – – – CDKN1B 4 1.6 9 3.7 – – CDKN2A 70 28.6 36 14.7 2 0.8 CDKN2B 5 2 28 11.4 – – CDKN2C – – 3 1.2 – – CEBPA 1 0.4 21 8.6 – – CHEK1 3 1.2 1 0.4 – – CHEK2 7 2.9 1 0.4 – – CHUK 10 4.1 – – – – CIC 17 6.9 3 1.2 – – CRBN 5 2 – – – – CREBBP 22 9 – – – – CRKL – – 8 3.3 1 0.4 CRLF2 – – 3 1.2 – – CSF1R 16 6.5 1 0.4 – – CTCF 6 2.4 – – – – CTNNA1 9 3.7 – – – – CTNNB1 3 1.2 – – – – CUL4A 2 0.8 7 2.9 1 0.4 CUL4B 6 2.4 – – – – CYP17A1 1 0.4 1 0.4 – – © 2018 American Medical Association.