Calvin Zippin

Radiation therapy for cervical cancer: Late effects on life span and on leukemia incidence

To investigate life‐shortening after partial body exposure, survival of 497 patients whose primary treatment was exclusively with x‐rays and radium for squamous cell cancer of the cervix (localized and regional stages) is under continuing study. To eliminate early deaths due to cancer and to provide maximal follow‐up time, the group includes only those who survived at least 5 years and who were under age 55 at time of diagnosis. The patients were treated in 1932–1951 and were drawn from the University of California and Connecticut State Tumor Registries. Pelvic regional dose was calculated for each patient. Three dose‐groups were formed: < 23 Mgm‐rads, 23–31 Mgm‐rads, and 32–54 Mgm‐rads. When dose groups were compared with one another within stage and registry, and also after pooling stages and registries, no statistically significant differences in survival were found. When uterine cancer deaths were excluded to adjust for the possibility that unsuccessful treatment might have masked the life‐shortening effect under study, again no association was found between radiation dosage and survival. In excess of 7 cases of leukemia were predicted for the 10‐year period of 5 to 14 years after treatment. To this time, no deaths have been attributed to leukemia.

The prognostic significance of palpable lymph nodes in cancer of the breast

Examination of descriptive information on more than 2000 patients with mammary cancer led to the identification of a relatively small group of patients in which the clinical manifestations and the associated survival experience suggest the influence of a host defensive mechanism. A total of 100 patients were reported to have bilateral palpable axillary nodes. After accounting for the influence of other factors, it was found that this condition is associated with favorable prognosis. Specifically, the survival of patients with bilateral palpable nodes was as favorable as that for patients with no palpable nodes and clearly more favorable than for patients with palpable homolateral nodes. In itself, the presence of bilateral palpable nodes is not necessarily associated with a good prognosis. More than half of these patients were found to have pathologically positive homolateral axillary nodes; such a finding is an overriding unfavorable condition. However, even among patients with pathologically positive nodes, bilateral palpable nodes tended to improve prognosis. Among patients with pathologically negative nodes, the survival of those with bilateral palpable nodes was somewhat more favorable than for patients with no palpable nodes. The data suggest that bilateral palpable nodes may be a manifestation of a host defensive response. This may be a useful lead for further research concerning the host defense mechanism in cancer of the breast.

Identification of high risk groups in breast cancer.

In addition to a brief review of earlier work on the epidemiology of breast cancer, recently observed genetic, socioeconomic, and viral associations with this disease are discussed here.

Computer-Aided Prognosis

Publisher Summary This chapter presents a comparison of several ways to predict survival following diagnosis and treatment of a disease. It discusses alternative estimators of the five-year survival rate and compares their performance on a large group of breast cancer cases. The chapter presents a density estimation method and a standard method for the estimation of the five-year survival rate and then compares several other regression methods for the same problem. The density estimation method has two advantages over the regression methods: (1) incomplete data can be used, and (2) rough estimates of the accuracy of the probability assessments are available. The regression method also has two advantages over the density estimation method: (1) regression of survival time on indicants retains detailed information about survival times, which density estimation methods lose by dichotomizing survival time, and (2) a regression method can furnish a probability distribution of survival time, given an array of indicants.