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Prior cancer does not adversely affect survival in locally advanced lung cancer: A national SEER-medicare analysis.

ABSTRACT: Management of locally advanced non-small cell lung cancer is among the most highly contested areas in thoracic oncology. In this population, a history of prior cancer frequently results in exclusion from clinical trials and may influence therapeutic decisions. We therefore determined prevalence and prognostic impact of prior cancer among these patients.We identified patients>65years of age diagnosed 1992-2009 with locally advanced lung cancer in the Surveillance, Epidemiology, and End Results-Medicare linked dataset. We characterized prior cancer by prevalence, type, stage, and timing. We compared all-cause and lung cancer-specific survival between patients with and without prior cancer using propensity score-adjusted Cox regression.51,542 locally advanced lung cancer patients were included; 15.8% had a history of prior cancer. Prostate (25%), gastrointestinal (17%), breast (16%), and other genitourinary (15%) were the most common types of prior cancer, and 76% percent of prior cancers were localized or in situ stage. Approximately half (54%) of prior cancers were diagnosed within 5 years of the index lung cancer date. Patients with prior cancer had similar (propensity-score adjusted hazard ratio [HR] 0.96; 95% CI, 0.94-0.99; P=0.005) and improved lung cancer-specific (HR 0.84; 95% CI, 0.81-0.86; P<0.001) survival compared to patients with no prior cancer.For patients with locally advanced lung cancer, prior cancer does not adversely impact clinical outcomes. Patients with locally advanced lung cancer and a history of prior cancer should not be excluded from clinical trials, and should be offered aggressive, potentially curative therapies if otherwise appropriate.

SUBMITTER: Laccetti AL

PROVIDER: S-EPMC4939247 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Prior cancer does not adversely affect survival in locally advanced lung cancer: A national SEER-medicare analysis.

Laccetti Andrew L AL Pruitt Sandi L SL Xuan Lei L Halm Ethan A EA Gerber David E DE

Lung cancer (Amsterdam, Netherlands) 20160531

<h4>Introduction</h4>Management of locally advanced non-small cell lung cancer is among the most highly contested areas in thoracic oncology. In this population, a history of prior cancer frequently results in exclusion from clinical trials and may influence therapeutic decisions. We therefore determined prevalence and prognostic impact of prior cancer among these patients.<h4>Materials and methods</h4>We identified patients>65years of age diagnosed 1992-2009 with locally advanced lung cancer in ...[more]

PMID: 27393515

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Project description:Background For patients with locally advanced breast cancer (LABC), conventional TNM staging is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making. Methods A retrospective analysis of 22,842 LABC patients was performed from 2010 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. An additional cohort of 200 patients from the Binzhou Medical University Hospital (BMUH) was analyzed. The least absolute shrinkage and selection operator (LASSO) regression was used to screen for variables. The identified variables were used to build a survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Results The LASSO analysis identified 9 variables in patients with LABC, including age, marital status, Grade, histological type, T-stage, N-stage, surgery, radiotherapy, and chemotherapy. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.767 [95% confidence intervals (95% CI): 0.751–0.775], cancer specific survival (CSS) was 0.765 (95% CI: 0.756–0.774). In the external validation cohort, the C-index of the nomogram in predicting the OS was 0.858 (95% CI: 0.812–0.904), the CSS was 0.866 (95% CI: 0.817–0.915). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1, 3, and 5-year OS were 0.836 (95% CI: 0.821–0.851), 0.769 (95% CI: 0.759–0.780), and 0.750 (95% CI: 0.738–0.762), respectively. The AUC values for prediction of the 1, 3, and 5-year CSS were 0.829 (95% CI: 0.811–0.847), 0.769 (95% CI: 0.757–0.780), and 0.745 (95% CI: 0.732–0.758), respectively. Results of the C-index, ROC curve, and DCA demonstrated that the nomogram was more accurate in predicting the OS and CSS of patients compared with conventional TNM staging. Conclusion Two prediction models were developed and validated in this study which provided more accurate prediction of the OS and CSS in LABC patients than the TNM staging. The constructed models can be used for predicting survival outcomes and guide treatment plans for LABC patients.

Project description:The optimal time to initiate adjuvant therapy (AT) in elderly patients with glioblastoma (GBM) remains unclear. We investigated the impact of timing to start AT on overall survival (OS) using two national-scale datasets covering elderly GBM populations in the United States. A total of 3159 and 8161 eligible elderly GBM patients were derived from the Surveillance, Epidemiology and End Results (SEER)-Medicare linked dataset (2004-2013) and the National Cancer Database (NCDB) (2004-2014), respectively. The intervals in days from the diagnosis to the initiation of AT were categorized based on two scenarios: Scenario I (quartiles), ≤ 15, 16-26, 27-37, and ≥ 38 days; Scenario II (median), < 27, and ≥ 27 days. The primary outcome was OS. We performed the Kaplan-Meier and Cox proportional hazards regression methods for survival analysis. A sensitivity analysis was performed using Propensity Score Matching (PSM) method to achieve well-balanced characteristics between early-timing and delayed-timing in Scenario II. Improved OS was observed among patients who underwent resection and initiated AT with either a modest delay (27-37 days) or a longer delay (≥ 38 days) compared to those who received AT immediately (≤ 15 days) from both the SEER-Medicare dataset [adjusted hazard ratio (aHR) 0.74, 95% CI 0.64-0.84, P < 0.001; and aHR 0.81, 95% CI 0.71-0.92, P = 0.002] and the NCDB (aHR 0.83, 95% CI 0.74-0.93, P = 0.001; and aHR 0.87, 95% CI 0.77-0.98, P = 0.017). The survival advantage is observed in delayed-timing group as well in Scenario II. For elderly patients who had biopsy only, improved OS was only detected in a longer delay (Scenario I: ≥ 38 days vs. ≤ 15 days) or the delayed-timing group (Scenario II: ≥ 27 days vs. < 27 days) in the NCDB while no survival difference was seen in SEER-Medicare population. For the best timing to start AT in elderly GBM patients, superior survivals were observed among those who had craniotomy and initiated AT with a modest (27-37 days) or longer delays (≥ 38 days) following diagnosis using both the SEER-Medicare and NCDB datasets (Scenario I). Such survival advantage was confirmed when categorizing delayed-timing vs. early-timing with the cut-off at 27 day in both datasets (Scenario II). The increased likelihood of receiving delayed AT (≥ 27 days) was significantly associated with tumor resection (STR/GTR), years of diagnosis after 2006, African American and Hispanics races, treatments at academic facilities, and being referred. There is no difference in timing of AT on survival among elderly GBM patients who had biopsy in the SEER-Medicare dataset. In conclusion, initiating AT with a modest delay (27-37 days) or a longer delay (≥ 38 days) after craniotomy may be the preferred timing in the elderly GBM population.

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Prior cancer does not adversely affect survival in locally advanced lung cancer: A national SEER-medicare analysis.

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Prior cancer does not adversely affect survival in locally advanced lung cancer: A national SEER-medicare analysis.

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