Search

Background: Metastatic non‐small cell lung cancer (NSCLC) is mostly seen in older patients and is associated with poor prognosis. There is no reliable method to predict the prognosis of elderly patients (≥60 years old) with metastatic NSCLC. The aim of our study was to develop and validate nomograms which accurately predict survival in this group of patients. Methods: NSCLC patients diagnosed between 2010 and 2015 were all identified from the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms were constructed by significant clinicopathological variables (p < 0.05) selected in multivariate Cox analysis regression. Results: A total of 9584 patients met the inclusion criteria and were randomly allocated in the training (n = 6712) and validation (n = 2872) cohorts. In training cohort, independent prognostic factors included age, gender, race, grade, tumor site, pathology, T stage, N stage, radiotherapy, surgery, chemotherapy, and metastatic site (p < 0.05) for lung cancer‐specific survival (LCSS) and overall survival (OS) were identified by the Cox regression. Nomograms for predicting 1‐, 2‐, and 3‐years LCSS and OS were established and showed excellent predictive performance with a higher C‐index than that of the 7th TNM staging system (LCSS: training cohort: 0.712 vs. 0.534; p < 0.001; validation cohort: 0.707 vs. 0.528; p < 0.001; OS: training cohort: 0.713 vs. 0.531; p < 0.001; validation cohort: 0.710 vs. 0.528; p < 0.001). The calibration plots showed good consistency from the predicted to actual survival probabilities both in training cohort and validation cohort. Moreover, the decision curve analysis (DCA) achieved better net clinical benefit compared with TNM staging models. Conclusions: We established and validated novel nomograms for predicting LCSS and OS in elderly patients with metastatic NSCLC with desirable discrimination and calibration ability. These nomograms could provide personalized risk assessment for these patients and assist in clinical decision. [ABSTRACT FROM AUTHOR]

Introduction: Lung transplantation has proven to be an effective treatment option for end‐stage lung disease. However, early and late complications following transplantation remain significant causes of high mortality. Objectives: In this review, we focus on the time of onset in primary graft dysfunction and rejection complications, as well as emphasize the role of imaging manifestations and pathological features in early diagnosis, thus assisting clinicians in the early detection and treatment of posttransplant complications and improving patient quality of life and survival. Data source: We searched electronic databases such as PubMed, Web of Science, and EMBASE. We used the following search terms: lung transplantation complications, primary graft dysfunction, acute rejection, chronic lung allograft dysfunction, radiological findings, and diagnosis and treatment. Conclusion: Primary graft dysfunction, surgical complications, immune rejection, infections, and neoplasms represent major posttransplant complications. As the main posttransplant survival limitation, chronic lung allograft dysfunction has a characteristic imaging presentation; nevertheless, the clinical and imaging manifestations are often complex and overlap, so it is essential to understand the temporal evolution of these complications to narrow the differential diagnosis for early treatment to improve prognosis. Early and late complications after lung transplantation remain essential causes of high mortality. In this review, we focus on the timing of the onset of primary graft dysfunction and rejection complications and highlight the role of imaging manifestations and clinicopathologic features in early diagnosis, thus assisting clinicians in the early detection and treatment of posttransplant complications and improving patient quality of life and survival. [ABSTRACT FROM AUTHOR]