Utilization of target lesion heterogeneity for treatment efficacy assessment in late stage lung cancer

Abstract

Rationale Recent studies have discovered several unique tumor response subgroups outside of response classification by Response Evaluation Criteria for Solid Tumors (RECIST), such as mixed response and oligometastasis. These subtypes have a distinctive property, lesion heterogeneity defined as diversity of tumor growth profiles in RECIST target lesions. Furthermore, many cancer clinical trials have been activated to evaluate various treatment options for heterogeneity-related subgroups (e.g., 29 trials so far listed in clinicaltrials.gov for cancer patients with oligometastasis). Some of the trials have shown survival benefit by tailored treatment strategies. This evidence presents the unmet need to incorporate lesion heterogeneity to improve RECIST response classification. Method An approach for Lesion Heterogeneity Classification (LeHeC) was developed using a contemporary statistical approach to assess target lesion variation, characterize patient treatment response, and translate informative evidence to improving treatment strategy. A mixed effect linear model was used to determine lesion heterogeneity. Further analysis was conducted to classify various types of lesion variation and incorporate with RECIST to enhance response classification. A study cohort of 110 target lesions from 36 lung cancer patients was used for evaluation. Results Due to small sample size issue, the result was exploratory in nature. By analyzing RECIST target lesion data, the LeHeC approach detected a high prevalence (n = 21; 58%) of lesion heterogeneity. Subgroup classification revealed several informative distinct subsets in a descending order of lesion heterogeneity: mix of progression and regression (n = 7), mix of progression and stability (n = 9), mix of regression and stability (n = 5), and non-heterogeneity (n = 15). Evaluation for association of lesion heterogeneity and RECIST best response classification showed lesion heterogeneity commonly occurred in each response group (stable disease: 16/27; 59%; partial response: 3/5; 60%; progression disease: 2/4; 50%). Survival analysis showed a differential trend of overall survival between heterogeneity and non-heterogeneity in RECIST response groups. Conclusion This is the first study to evaluate lesion heterogeneity, an underappreciated metric, for RECIST application in oncology clinical trials. Results indicated lesion heterogeneity is not an uncommon event. The LeHeC approach could enhance RECIST response classification by utilizing granular lesion level discovery of heterogeneity.

Intervention model under the Omaha system framework can effectively improve the sleep quality and negative emotion of patients with mid to late-stage lung cancer and is a protective factor for quality of life

“…The treatment process of mid to late-stage LC involves not only chemotherapy, molecular targeted therapy, immunotherapy, anticancer drug therapy, and nutritional therapy, but also care measures to prolong the survival time, improve QoL, alleviate pain, and prevent complications [21,22]. However, traditional care methods have limitations including the lack of continuous and personalized care support after discharge, insufficient intervention addressing sleep quality, exercise, and mental health, and the possible lack of systematic and structured care practices, which compromise the rehabilitation and QoL of patients [23].…”

Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?

“…Typically, a lung micro nodule may be considered as NTL by one reader while the paired reader may not consider the finding significant (see example in Figure 8 ) which could potentially lead to a discrepancy in evaluating the extent of disease. Indeed, during the follow-up, some of the differences between readers in capturing disease progression have been explained by possible dissociation of the response i.e., when tumors selected from different disease locations respond differently to treatment ( 24 , 25 ). In trials evaluating the efficacy of immunotherapy, a dissociated response has been reported in 30% of patients for our indication ( 26 ).…”