A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients.
OBJECTIVE
Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient.


METHODS
Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130).


RESULTS
The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability (www.predictcancer.org). The data set can be downloaded at https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048.


CONCLUSIONS
The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.
Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht, The Netherlands. Electronic address: cary.oberije@maastro.nl.
Cary
C
Oberije
Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht, The Netherlands; Universitaire Ziekenhuizen Leuven, KU Leuven, Belgium.
Dirk
D
De Ruysscher
Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht, The Netherlands.
Ruud
R
Houben
Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
Michel
M
van de Heuvel
Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
Wilma
W
Uyterlinde
Memorial Sloan Kettering Cancer Center, New York.
Joseph O
JO
Deasy
Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
Jose
J
Belderbos
Department of Pulmonology, University Hospital Maastricht, Research Institute GROW of Oncology, Maastricht, The Netherlands.
Anne-Marie C
AM
Dingemans
Memorial Sloan Kettering Cancer Center, New York.
Andreas
A
Rimner
Memorial Sloan Kettering Cancer Center, New York.
Shaun
S
Din
Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht, The Netherlands.
Philippe
P
Lambin
D000367:Age Factors; D000368:Aged; D000704:Analysis of Variance; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D016190:Carboplatin / Q000008:administration & dosage; D002289:Carcinoma, Non-Small-Cell Lung / Q000401:mortality / Q000473:pathology / Q000628:therapy; D059248:Chemoradiotherapy / Q000379:methods* / Q000401:mortality; D002945:Cisplatin / Q000008:administration & dosage; D003841:Deoxycytidine / Q000008:administration & dosage / Q000031:analogs & derivatives; D005047:Etoposide / Q000008:administration & dosage; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009367:Neoplasm Staging; D049451:Nomograms; D011336:Probability; D011879:Radiotherapy Dosage; D012044:Regression Analysis; D012720:Severity of Illness Index; D012737:Sex Factors; D014747:Vinblastine / Q000008:administration & dosage / Q000031:analogs & derivatives; D000077235:Vinorelbine; D000093542:Gemcitabine
D003841:Deoxycytidine; D014747:Vinblastine; D005047:Etoposide; D016190:Carboplatin; D002945:Cisplatin; D000077235:Vinorelbine; D000093542:Gemcitabine