Andrew Warner1, Max Dahele2, Bo Hu1, David A Palma1, Suresh Senan2, Cary Oberije3, Kayoko Tsujino4, Marta Moreno-Jimenez5, Tae Hyun Kim6, Lawrence B Marks7, Ramesh Rengan8, Luigi De Petris9, Sara Ramella10, Kim De Ruyck11, Núria Rodriguez De Dios12, Jeffrey D Bradley13, George Rodrigues14. 1. Department of Radiation Oncology, London Health Sciences Centre, London, Ontario, Canada. 2. Department of Radiation Oncology, VU University Medical Center, Amsterdam, The Netherlands. 3. Department of Radiation Oncology, MAASTRO Clinic, Maastricht, The Netherlands. 4. Department of Radiation Oncology, Hyogo Cancer Center, Akashi, Japan. 5. Department of Oncology, Clínica Universidad, Universidad de Navarra, Pamplona, Spain. 6. Department of Radiation Oncology, National Cancer Center, Goyang-si, Gyeonggi, Korea. 7. Department of Radiation Oncology, University of North Carolina Chapel Hill, Chapel Hill, North Carolina. 8. Department of Radiation Oncology, University of Washington, Seattle, Washington. 9. Department of Oncology and Pathology, Karolinska University Hospital, Stockholm, Sweden. 10. Department of Radiation Oncology, Campus Bio-Medico University, Rome, Italy. 11. Department of Basic Medical Sciences, Ghent University, Ghent, Belgium. 12. Department of Radiation Oncology, Hospital de la Esperanza, Parc de Salut Mar, Barcelona, Spain. 13. Department of Radiation Oncology, Washington University School of Medicine, St Louis, Missouri. 14. Department of Radiation Oncology, London Health Sciences Centre, London, Ontario, Canada. Electronic address: George.Rodrigues@lhsc.on.ca.
Abstract
PURPOSE: Concurrent chemoradiation therapy (con-CRT) is recommended for fit patients with locally advanced non-small cell lung cancer (LA-NSCLC) but is associated with toxicity, and observed survival continues to be limited. Identifying factors associated with early mortality could improve patient selection and identify strategies to improve prognosis. METHODS AND MATERIALS: Analysis of a multi-institutional LA-NSCLC database consisting of 1245 patients treated with con-CRT in 13 institutions was performed to identify factors predictive of 180-day survival. Recursive partitioning analysis (RPA) was performed to identify prognostic groups for 180-day survival. Multivariate logistic regression analysis was used to create a clinical nomogram predicting 180-day survival based on important predictors from RPA. RESULTS: Median follow-up was 43.5 months (95% confidence interval [CI]: 40.3-48.8) and 127 patients (10%) died within 180 days of treatment. Median, 180-day, and 1- to 5-year (by yearly increments) actuarial survival rates were 20.9 months, 90%, 71%, 45%, 32%, 27%, and 22% respectively. Multivariate analysis adjusted by region identified gross tumor volume (GTV) (odds ratio [OR] ≥100 cm(3): 2.61; 95% CI: 1.10-6.20; P=.029) and pulmonary function (forced expiratory volume in 1 second [FEV1], defined as the ratio of FEV1 to forced vital capacity [FVC]) (OR <80%: 2.53; 95% CI: 1.09-5.88; P=.030) as significant predictors of 180-day survival. RPA resulted in a 2-class risk stratification system: low-risk (GTV <100 cm(3) or GTV ≥100 cm(3) and FEV1 ≥80%) and high-risk (GTV ≥100 cm(3) and FEV1 <80%). The 180-day survival rates were 93% for low risk and 79% for high risk, with an OR of 4.43 (95% CI: 2.07-9.51; P<.001), adjusted by region. A clinical nomogram predictive of 180-day survival, incorporating FEV1, GTV, N stage, and maximum esophagus dose yielded favorable calibration (R(2) = 0.947). CONCLUSIONS: This analysis identified several risk factors associated with early mortality and suggests that future research in the optimization of pretreatment pulmonary function and/or functional lung avoidance treatment may alter the therapeutic ratio in this patient population.
PURPOSE: Concurrent chemoradiation therapy (con-CRT) is recommended for fit patients with locally advanced non-small cell lung cancer (LA-NSCLC) but is associated with toxicity, and observed survival continues to be limited. Identifying factors associated with early mortality could improve patient selection and identify strategies to improve prognosis. METHODS AND MATERIALS: Analysis of a multi-institutional LA-NSCLC database consisting of 1245 patients treated with con-CRT in 13 institutions was performed to identify factors predictive of 180-day survival. Recursive partitioning analysis (RPA) was performed to identify prognostic groups for 180-day survival. Multivariate logistic regression analysis was used to create a clinical nomogram predicting 180-day survival based on important predictors from RPA. RESULTS: Median follow-up was 43.5 months (95% confidence interval [CI]: 40.3-48.8) and 127 patients (10%) died within 180 days of treatment. Median, 180-day, and 1- to 5-year (by yearly increments) actuarial survival rates were 20.9 months, 90%, 71%, 45%, 32%, 27%, and 22% respectively. Multivariate analysis adjusted by region identified gross tumor volume (GTV) (odds ratio [OR] ≥100 cm(3): 2.61; 95% CI: 1.10-6.20; P=.029) and pulmonary function (forced expiratory volume in 1 second [FEV1], defined as the ratio of FEV1 to forced vital capacity [FVC]) (OR <80%: 2.53; 95% CI: 1.09-5.88; P=.030) as significant predictors of 180-day survival. RPA resulted in a 2-class risk stratification system: low-risk (GTV <100 cm(3) or GTV ≥100 cm(3) and FEV1 ≥80%) and high-risk (GTV ≥100 cm(3) and FEV1 <80%). The 180-day survival rates were 93% for low risk and 79% for high risk, with an OR of 4.43 (95% CI: 2.07-9.51; P<.001), adjusted by region. A clinical nomogram predictive of 180-day survival, incorporating FEV1, GTV, N stage, and maximum esophagus dose yielded favorable calibration (R(2) = 0.947). CONCLUSIONS: This analysis identified several risk factors associated with early mortality and suggests that future research in the optimization of pretreatment pulmonary function and/or functional lung avoidance treatment may alter the therapeutic ratio in this patient population.
Authors: Maja Guberina; Wilfried Eberhardt; Martin Stuschke; Thomas Gauler; Clemens Aigner; Martin Schuler; Georgios Stamatis; Dirk Theegarten; Walter Jentzen; Ken Herrmann; Christoph Pöttgen Journal: Eur J Nucl Med Mol Imaging Date: 2019-02-01 Impact factor: 9.236
Authors: Lisa Ni; Matthew Koshy; Philip Connell; Sean Pitroda; Daniel W Golden; Hania Al-Hallaq; Greg Hubert; Greg Kauffman; Anne McCall; Renuka Malik Journal: J Thorac Dis Date: 2019-06 Impact factor: 2.895