br The inclusion of these variables itself
The inclusion of these variables itself is not surprising, as multiple studies have shown that these factors are individual prognostic markers in lung cancer. In an analysis of the international staging database of the International Association for the Study of Lung Cancer, Sculier et al. an-alyzed records of 12,428 patients . Similar to the findings of the present analysis, they found that male gender was associated with an increased risk of death, after adjusting for clinical stage, age, PS, and his-tology (HR - 1.17, 95% CI, 1.11, 1.23; p b .001).
The present study did not stage patients according to the AJCC 7th Edition, as the majority of the trials included in the analysis were com-pleted prior to the use of this system. Stage IIIB in the present analysis includes patients who would be considered as having M1a disease (stage IV) in the AJCC 7th Edition TNM classification. Nevertheless, we found a significantly increased risk of death in patients with distant me-tastases (Stage IV in the previous AJCC classification; Stage IV - M1b in the 7th Edition). This further highlights the prognostic significance of intrathoracic as opposed extra-thoracic metastatic disease.
Geriatric assessment of all older patients with cancer prior to treat-ment, has been recommended as a way to detect hitherto hidden health problems even in those with a good performance status . A recent study analyzed the prognostic value of the Geriatric 8 (G8) assessment in older patients with lung cancer. In this analysis of 142 patients (84 with NSCLC), the potentially frail patients had a significantly greater risk of 1-year mortality (hazard ratio, 4.08; 95% confidence interval 1.67–9.99; P = .02). The only other significant variable was a higher dis-ease stage. While geriatric assessment may provide a useful approach to identifying older patients with lung cancer at risk for early mortality, it TAK-242 is time consuming and hence its incorporation in routine clinical care has been limited.
The main strengths of this study are the large sample size and its de-velopment using data only from older individuals. Despite the simplicity of the model, its performance characteristics are similar to the presently available models, namely the Blanchon and Mandrekar models. Also since the variables in the present model are routinely captured as part of clinical care, it does not increase the burden on the oncologist or clinic staff. Hence this can be used routinely to determine prognosis of older
Fig. 2. Overall survival based on risk stratification among older patients with advanced non-small cell lung cancer (a) training set; (b) testing set.
patients with advanced NSCLC, especially if a comprehensive geriatric assessment is not feasible. Furthermore, a simpler model can be more robust and therefore more useful as compared to a complex model, in which additional predictors are included but have low added value in prediction accuracy. The limitations of this study include that it comprised of only those patients, who were enrolled in NCI cooperative group clinical trials. Pre-vious studies have indicated that patients approached for clinical trial participation may have certain specific characteristics and may not nec-essarily represent the population at large . However, given the di-verse nature of enrollment in cooperative group trials, we feel that our
Area under 1-, 2- year ROC and C-index in training and testing cohorts.
ROC – Receiver Operating Characteristics.
CI – Confidence Interval.
findings are valuable to the practicing oncologist. In addition, this model would help the development of practical clinical trials for older adults with advanced NSCLC.
Secondly, most of the trials included in this analysis were conducted before current knowledge regarding specific driver mutations and im-munotherapeutic agents were available and hence that information is lacking. Lastly, the clinical trials included in this analysis did not have a component of geriatric assessment. Nonetheless, we believe that this information will be valuable as the same parameters will be relevant to those patients as well.