Early tumor shrinkage identifies long-term disease control and survival in patients with lung cancer treated with atezolizumab

Abstract

BackgroundPreliminary evidence indicates that early tumor shrinkage (ETS) following immune checkpoint inhibitor (ICI) initiation may be associated with survival outcomes in patients with advanced melanoma. ETS has not been explored as a biomarker of survival outcomes or patient-reported outcomes in patients with advanced non-small cell lung cancer (NSCLC) treated with ICIs.MethodsThe study pooled data from patients with NSCLC in the randomized trials OAK and POPLAR (atezolizumab vs docetaxel; n=1464), and single-arm atezolizumab trials BIRCH and FIR (n=797). The association between ETS (≥10% decrease in pretreatment sum-of-longest diameters of target-lesions at 6 weeks) and overall survival (OS), progression-free survival (PFS), time to deterioration (TDD) in health-related quality-of-life (HRQoL) and physical function (PF) was assessed using Cox proportional hazard analysis.ResultsETS occurred in 20% of atezolizumab-treated patients with NSCLC within OAK and POPLAR and was associated with highly favorable OS (HR 0.33, p<0.001), PFS (HR 0.31, p<0.001), TDD in HRQoL (HR 0.73, p=0.01) and PF (HR 0.52, p<0.001). The results were replicated in the BIRCH and FIR data. Atezolizumab-treated patients achieving ETS had markedly improved OS compared with docetaxel-treated patients achieving ETS (24-month OS 55% vs 32%); PFS was also markedly improved (24-month PFS 31% vs 4%). In contrast, for patients not achieving ETS, atezolizumab-treatment was associated with more modest OS (24-month OS 23% vs 20%) and PFS (24-month PFS 3% vs 1%) improvement compared with docetaxel. Overall, the effect size for ETS within the atezolizumab-treated patients was significantly greater than that in the docetaxel-treated patients (P(interaction)=0.002 for OS and P(interaction)<0.001 for PFS).ConclusionsETS is an easily measurable biomarker, predictive of highly favorable survival and patient-reported outcomes with atezolizumab treatment for advanced NSCLC. Further, ETS identifies patients with significantly greater treatment benefit for ICI therapy.

Prognostic impact of early tumor shrinkage and depth of response in patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors

“…Our observation about the association of ETS with survival outcomes is in line with previously reported data in patients with other tumor types treated with ICIs. [15][16][17] Of note, some of these previous studies are limited by the inclusion of patients with primary progressive diseasewho have an extremely poor survival-in the subgroup without ETS, thus magnifying the prognostic impact of ETS itself. Here, we decided to properly restrict our focus on patients with disease control at the first radiological reassessment, as in the work of Kawachi et al 16 From a clinical perspective, we observed that patients treated with anti-PD-1 monotherapy and not achieving ETS at the 8/9 weeks time point had a clearly and significantly worse outcome as compared with other patients.…”

Integrative evaluation of primary and metastatic lesion spectrum to guide anti-PD-L1 therapy of non-small cell lung cancer: results from two randomized studies

“…To be specific, regarding accessibility, baseline tumor burden and metastatic sites are readily available at diagnosis through image examinations without additional and subsequent tests, whereas early tumor shrinkage should be assessed at the six-week visit. 11 As for stability, the primary and metastatic lesion spectrum would not be disturbed by the short-term physical condition, whilst hematological markers (e.g. LIPI 7 , 8 and CRP 10 ) might be affected by infection, trauma, and the usage of glucocorticoids or antibiotics, etc.…”

“… 3 , 4 Thus, numerous parameters predicting ideal candidates for second-line ICI treatment have been identified as potential markers, 5 encompassing body mass index (BMI), 6 neutrophil and lymphocyte count number (LIPI), 7 , 8 C-reactive protein (CRP), 9 patient-reported physical function. 10 Still, efforts to establish effective markers from other dimensions, specially from image examinations, 11 are warranted to complement the field and promote precision medicine.…”

Application of Machine Learning for Tumor Growth Inhibition – Overall Survival Modeling Platform

“…The TGI metrics used in the models were previously derived based on tumor size data 13 and have been shown to capture treatment effect and could be considered as a predictive biomarker for OS. [11][12][13]35 The four ML methods evaluated in the analysis included covariate/feature selection and prediction, where feature selection builds a screening model by removing the redundant features. In traditional modeling approaches, the rule of parsimony dictates a goal of finding the fewest number of variables that can accurately predict outcome for model stability, even though important information may be lost if variables that are not sufficiently predictive are excluded from the model.…”

“…The dataset would not be considered high‐dimensional for ML analysis, but the application of ML approaches to the data could nevertheless provide comparative insights. The TGI metrics used in the models were previously derived based on tumor size data 13 and have been shown to capture treatment effect and could be considered as a predictive biomarker for OS 11–13,35 …”