Prognosis in lung cancer: physicians' opinions compared with outcome and a predictive model

Although the study of prognostic factors in small cell lung cancer has reached the stage where they are used to guide treatment, fewer data are available for non-small cell lung cancer. Although correct management decisions in non-small cell lung cancer depend upon a prognostic assessment by the supervising doctor, there has never been any measurement of the accuracy of physicians' assessments.

A group of consecutive patients with non-small cell lung cancer was studied and the predictions of their physicians as to how long they would survive (in months) was compared with their actual survival. A prognostic index was also developed using features recorded at the patients' initial presentation.

Two hundred and seven consecutive patients diagnosed and managed as non-small cell lung cancer, who did not receive curative treatment for their condition, were studied. Of the 196 patients whose date of death was known, physicians correctly predicted, to within one month, the survival of only 19 patients (10%). However, almost 59% of patients (115/196) had their survival predicted to within three months and 71% (139/196) to within four months of their actual survival. Using Cox's regression model, the sex of the patient, the activity score, the presence of malaise, hoarseness and distant metastases at presentation, and lymphocyte count, serum albumin, sodium and alkaline phosphatase levels were all identified as useful prognostic factors. Three groups of patients, distinct in terms of their survival, were identified by the use of these items. When the prediction of survival made by the physician was included as a prognostic factor in the original model, it was shown to differentiate further between the group with a poor prognosis and the other two groups in terms of survival.

Physicians were highly specific in identifying patients who would live less than three months. However, they had a tendency to overestimate survival in these patients, failing to identify almost half the patients who actually died within this time. Both the physicians and the prognostic factor model gave similar performances in that they were more successful in identifying patients who had a short time to survive than those who had a moderate or good prognosis. Physicians appear to use information not identified in the prognostic factor analysis to reach their conclusions.