Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325).
OBJECTIVE
Currently, prediction of survival for non-small-cell lung cancer patients treated with (chemo)radiotherapy is mainly based on clinical factors. The hypothesis of this prospective study was that blood biomarkers related to hypoxia, inflammation, and tumor load would have an added prognostic value for predicting survival.


METHODS
Clinical data and blood samples were collected prospectively (NCT00181519, NCT00573040, and NCT00572325) from 106 inoperable non-small-cell lung cancer patients (Stages I-IIIB), treated with curative intent with radiotherapy alone or combined with chemotherapy. Blood biomarkers, including lactate dehydrogenase, C-reactive protein, osteopontin, carbonic anhydrase IX, interleukin (IL) 6, IL-8, carcinoembryonic antigen (CEA), and cytokeratin fragment 21-1, were measured. A multivariate model, built on a large patient population (N = 322) and externally validated, was used as a baseline model. An extended model was created by selecting additional biomarkers. The model's performance was expressed as the area under the curve (AUC) of the receiver operating characteristic and assessed by use of leave-one-out cross validation as well as a validation cohort (n = 52).


RESULTS
The baseline model consisted of gender, World Health Organization performance status, forced expiratory volume, number of positive lymph node stations, and gross tumor volume and yielded an AUC of 0.72. The extended model included two additional blood biomarkers (CEA and IL-6) and resulted in a leave-one-out AUC of 0.81. The performance of the extended model was significantly better than the clinical model (p = 0.004). The AUC on the validation cohort was 0.66 and 0.76, respectively.


CONCLUSIONS
The performance of the prognostic model for survival improved markedly by adding two blood biomarkers: CEA and IL-6.
Dehing-Oberije
Cary
C
Department of Radiation Oncology (MAASTRO Clinic), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands. cary.dehing@maastro.nl
Aerts
Hugo
H
Yu
Shipeng
S
De Ruysscher
Dirk
D
Menheere
Paul
P
Hilvo
Mika
M
van der Weide
Hiska
H
Rao
Bharat
B
Lambin
Philippe
P
D000368:Aged; D000951:Antigens, Neoplasm / Q000097:blood; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000097:blood*; D002097:C-Reactive Protein / Q000032:analysis; D002256:Carbonic Anhydrases / Q000097:blood; D002272:Carcinoembryonic Antigen / Q000097:blood; D002289:Carcinoma, Non-Small-Cell Lung / Q000097:blood* / Q000188:drug therapy / Q000401:mortality* / Q000473:pathology / Q000532:radiotherapy; D003131:Combined Modality Therapy / Q000379:methods / Q000401:mortality; D005260:Female; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000401:mortality; D015850:Interleukin-6 / Q000097:blood; D016209:Interleukin-8 / Q000097:blood; D053539:Keratin-19 / Q000097:blood; D007770:L-Lactate Dehydrogenase / Q000097:blood; D008175:Lung Neoplasms / Q000097:blood* / Q000188:drug therapy / Q000401:mortality* / Q000473:pathology / Q000532:radiotherapy; D008297:Male; D015233:Models, Statistical; D009367:Neoplasm Staging / Q000379:methods; D053495:Osteopontin / Q000097:blood; D011379:Prognosis; D011446:Prospective Studies; D047368:Tumor Burden
D000951:Antigens, Neoplasm; D014408:Biomarkers, Tumor; D002272:Carcinoembryonic Antigen; D015850:Interleukin-6; D016209:Interleukin-8; D053539:Keratin-19; C102012:antigen CYFRA21.1; D053495:Osteopontin; D002097:C-Reactive Protein; D007770:L-Lactate Dehydrogenase; D002256:Carbonic Anhydrases