Novel Nutrition-Based Nomograms to Assess the Outcomes of Lung Cancer Patients Treated With Anlotinib or Apatinib

Abstract

BackgroundPrevious studies have indicated that the changes in body composition during treatment are prognostic in lung cancer. The question which follows is it may be too late to identify vulnerable patients after treatment and to improve outcomes for these patients. In our study, we sought to explore the alterations of body composition and weight before the outset of the antiangiogenic treatment and its role in predicting clinical response and outcomes.MethodsIn this retrospective study, 122 patients with advanced lung cancer treated with anlotinib or apatinib were analyzed. The changes in weight and body composition including skeletal muscle index (SMI), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) for 3 months before the outset of antiangiogenic treatment and other clinical characteristics were evaluated with LASSO Cox regression and multivariate Cox regression analysis, which were applied to construct nomograms. The performance of the nomograms was validated internally by using bootstrap method with 1,000 resamples models and was assessed by the concordance index (C-index), calibration plots, decision curve analysis (DCA).ResultsThe median progression-free survival (PFS) and overall survival (OS) were 128 (95% CI 103.2–152.8) days and 292 (95% CI 270.9–313.1) days. Eastern Cooperative Oncology Group performance status (ECOG PS), brain metastases, the Glasgow Prognostic Score (GPS), clinical response, therapeutic regimen, and ΔL1SMI per 90 days were significantly associated with PFS, while ECOG PS, GPS, clinical response, therapeutic regimen, ΔL1SMI per 90 days were identified for OS. The C-index for the nomograms of PFS and OS were 0.763 and 0.748, respectively. The calibration curves indicated excellent agreement between the predicted and actual survival outcomes of 3- and 4-month PFS and 7- and 8-month OS. DCA showed the considerable value of the model.ConclusionNomograms were developed from clinical features and nutritional indicators to predict the probability of achieving 3-month and 4-month PFS and 7-month and 8-month OS with antiangiogenic therapy for advanced lung cancer. Dynamic changes in body composition before the initiation of treatment contributed to early detection of poor outcome.