PurposeWeight loss is a well-recognized prognostic parameter for survival of lung cancer patients. Computerized-tomography (CT)-based analysis of body composition and blood-based metabolic evaluation are promising prognostic tools. We aimed to assess the correlation between albumin, body mass index (BMI), skeletal muscle mass index (SMI), fat-free mass index (FFMI), fat mass index (FMI) and weight change, as well as their correlation with survival of lung cancer patients on nivolumab treatment.MethodsData were retrospectively collected. Weight was measured at a diagnosis of stage 4 disease and before start of nivolumab. Albumin levels were measured before starting nivolumab. BMI, SMI, FFMI, and FMI were evaluated from CT scans performed at start of nivolumab. Overall survival (OS) was from starting of nivolumab to death or censured at last follow-up. Statistical analysis was done to identify correlation between the various factors and between those factors and survival.ResultsForty-six patients with advanced non-small cell lung cancer (NSCLC) were included. Median follow-up was 22 months. Pathology was Adenocarcinoma/Squamous/non-other specified in 25/15/6 respectively. All patients received nivolumab as an advanced-line treatment for stage IV NSCLC. We observed a significant correlation of weight loss (P=0.01, HR=2.85) and albumin (P=0.043, HR=0.34) with OS in multivariate analysis. A significant correlation was found between BMI to SMI, FFMI, FMI, and weight change.ConclusionWeight loss and low albumin levels are significant negative prognostic factors for NSCLC patients on immunotherapy. CT-based parameters of body composition remain to be proven as more reliable than standard clinical parameters.
BackgroundLittle is known regarding the efficacy of immune checkpoint inhibitors (ICI) in patients with advanced large-cell neuroendocrine lung carcinoma (aLCNEC).Methods125 consecutive patients with aLCNEC were identified in the electronic databases of 4 participating cancer centers. The patients were divided into group A (patients who received ICI, n=41) and group B (patients who did not receive ICI, n=84). Overall survival since advanced disease diagnosis (OS DX) and OS since ICI initiation (OS ICI) were captured.ResultsWith a median follow-up of 11.8 months (mo) (IQR 7.5–17.9) and 6.0mo (IQR 3.1–10.9), 66% and 76% of patients died in groups A and B, respectively. Median OS DX was 12.4mo (95% CI 10.7 to 23.4) and 6.0mo (95% CI 4.7 to 9.4) in groups A and B, respectively (log-rank test, p=0.02). For ICI administration, HR for OS DX was 0.59 (95% CI 0.38 to 0.93, p=0.02—unadjusted), and 0.58 (95% CI 0.34 to 0.98, p=0.04—adjusted for age, Eastern Cooperative Oncology Group (ECOG) performance status (PS), presence of liver metastases and chemotherapy administration). In a propensity score matching analysis (n=74; 37 patients in each group matched for age and ECOG PS), median OS DX was 12.5 mo (95% CI 10.6 to 25.2) and 8.4 mo (95% CI 5.4 to 16.9) in matched groups A and B, respectively (log-rank test, p=0.046). OS ICI for patients receiving ICI as monotherapy (n=36) was 11.0 mo (95% CI 6.1 to 19.4).ConclusionsWith the limitations of retrospective design and small sample size, the results of this real-world cohort analysis suggest a positive impact of ICI on OS in aLCNEC.
Purpose: Sleep is essential for life, as well as having a major impact on quality of life. Not much attention has been given to this important factor in the care of lung cancer patients. Patients and Methods: We retrospectively analyzed a cohort of 404 lung cancer patients treated in our institute between 2010 and 2018. Data about sleep quality, distress and pain were self-reported by questionnaires administered to patients at their first clinic visit to the Institute of Oncology. Sex, age, histology, stage, smoking and marital status were extracted from the patients' charts. Uni-and multi-variate analyses were carried out to evaluate the correlation of these factors with survival. Results: Most patients reported some level of distress and pain. Sleep abnormalities were reported by 58.7% of patients. Distress, pain and bad sleep were correlated with shorter survival in univariate analyses; however, only sleep remained associated with survival in multivariate analysis. Patients reporting bad sleep had a median survival of 16 months, compared to 27 months for patients reporting good sleep (hazard ratio 1.83, 95% C.I. 1.27-2.65). Frequent arousals at night were more tightly correlated with survival than difficulty falling asleep. Conclusion: Sleep quality, as reported by lung cancer patients, is highly correlated with survival. Further studies are required to comprehend whether poor sleep quality is directly impacting survival or is a result of the cancer aggressiveness and patients' conditions.
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