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)

PURPOSE

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 AND MATERIALS

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.

Development and external validation of prognostic model for 2-year survival of non-small-cell lung cancer patients treated with chemoradiotherapy

PURPOSE

Radiotherapy, combined with chemotherapy, is the treatment of choice for a large group of non-small-cell lung cancer (NSCLC) patients. Recent developments in the treatment of these patients have led to improved survival. However, the clinical TNM stage is highly inaccurate for the prediction of survival, and alternatives are lacking. The objective of this study was to develop and validate a prediction model for survival of NSCLC patients, treated with chemoradiotherapy.

PATIENTS AND METHODS

The clinical data from 377 consecutive inoperable NSCLC patients, Stage I-IIIB, treated radically with chemoradiotherapy were collected. A prognostic model for 2-year survival was developed, using 2-norm support vector machines. The performance of the model was expressed as the area under the curve of the receiver operating characteristic and assessed using leave-one-out cross-validation, as well as two external data sets.

RESULTS

The final multivariate model consisted of gender, World Health Organization performance status, forced expiratory volume in 1 s, number of positive lymph node stations, and gross tumor volume. The area under the curve, assessed by leave-one-out cross-validation, was 0.74, and application of the model to the external data sets yielded an area under the curve of 0.75 and 0.76. A high- and low-risk group could be clearly identified using a risk score based on the model.

CONCLUSION

The multivariate model performed very well and was able to accurately predict the 2-year survival of NSCLC patients treated with chemoradiotherapy. The model could support clinicians in the treatment decision-making process.

Tumor volume combined with number of positive lymph node stations is a more important prognostic factor than TNM stage for survival of non-small-cell lung cancer patients treated with (chemo)radiotherapy

PURPOSE

The current tumor, node, metastasis system needs refinement to improve its ability to predict survival of patients with non-small-cell lung cancer (NSCLC) treated with (chemo)radiation. In this study, we investigated the prognostic value of tumor volume and N status, assessed by using fluorodeoxyglucose-positron emission tomography (PET).

PATIENTS AND METHODS

Clinical data from 270 consecutive patients with inoperable NSCLC Stages I-IIIB treated radically with (chemo)radiation were collected retrospectively. Diagnostic imaging was performed using either integrated PET-computed tomography or computed tomography and PET separately. The Kaplan-Meier method, as well as Cox regression, was used to analyze data.

RESULTS

Univariate survival analysis showed that number of positive lymph node stations (PLNSs), as well as N stage on PET, was associated significantly with survival. The final multivariate Cox model consisted of number of PLNSs, gross tumor volume (i.e., volume of the primary tumor plus lymph nodes), sex, World Health Organization performance status, and equivalent radiation dose corrected for time; N stage was no longer significant.

CONCLUSIONS

Number of PLNSs, assessed by means of fluorodeoxyglucose-PET, was a significant factor for survival of patients with inoperable NSCLC treated with (chemo)radiation. Risk stratification for this group of patients should be based on gross tumor volume, number of PLNSs, sex, World Health Organization performance status, and equivalent radiation dose corrected for time.