Long-term survival rate of stages I-III small cell lung cancer patients in the SEER database-application of the lognormal model

Abstract

Many published studies for small cell lung cancer have short follow-up. Although published meta-analyses favor the use of prophylactic cranial irradiation (PCI) in complete responders, the degree of long-term benefit is not well established. Some studies show convergence of overall and disease-free survival curves with long-term follow-up of patients who received (PCI+) and did not receive PCI (PCI-), while other studies do not. We studied the long-term survival of small cell lung cancer patients in the Surveillance, Epidemiology and End Results (SEER) database, which is a population database and covers 26% of the United States population. A parametric statistical model, Boag’s lognormal model, was retrospectively validated, using the SEER data and the actuarial Kaplan-Meier method of calculation. The basis of the lognormal model is that the logarithm of survival times of cancer patients who died of their disease followed a normal distribution. From 1988–1991, there were 1060 incident cases of stages I-III small cell lung cancer in the 12 registry areas that comprise the SEER database, of whom 132 received (PCI+) and 928 did not receive PCI (PCI-). Two 2-year periods of diagnosis (1988–1989 and 1990–1991) were combined and then patients were followed-up for an additional two years. The first phase in the validation of the lognormal prediction model tested the goodness of fit of the survival times of those cancer patients, who died with their disease, to a lognormal distribution using a minimum chi-square method. The second phase used a maximum likelihood method to predict the long-term survival rate from short-term follow-up data and confirmed (validated) these results by Kaplan-Meier actuarial calculations using long-term available data. The survival time of uncured patients who received (PCI+) and did not receive PCI (PCI-) followed two different lognormal distributions. For PCI+ and PCI- patients respectively, the five-year cancer-specific survival rates, calculated using the Kaplan-Meier method and actual follow-up data to the year 2000, were 18 ± 3% and 12 ± 1%. The corresponding predictions, using the lognormal model were 15% and 11% respectively. The respective 10-year cancer-specific survival rates were 10 ± 3% and 9 ± 1%, when calculated by the Kaplan-Meier method, and 12% and 10% as predicted by the lognormal model. The available follow-up was not long enough to provide 15-year cancer-specific survival rates by the Kaplan-Meier method, but the lognormal model predicted them to be 12% and 10% respectively. The PCI+ and PCI- cancer-specific survival curves almost converged in long-term follow-up. The difference in the two survival curves, as calculated by the logrank test (which takes into account the whole duration of follow-up), was highly statistically significant (p < 0.001). The survival benefit with PCI is more apparent in the short-term, and diminishes with longer-term follow-up in the present study. The lognormal model has the potential to predict the results of on-going prospective PCI trials earlier than would be possible with the use of the Kaplan-Meier method. This may become a useful tool in outcome research