The contribution of statistical methods to cancer research

Article Abstract:

David Cox was the recipient of the 1990 Charles F. Kettering Award, given by the General Motors Cancer Research Foundation to recognize excellence in cancer research. Cox, whose name is now associated with the Cox proportional hazards method which he pioneered, has made contributions to the use of statistics in the analysis of cancer data. Clinical researchers are rarely able to focus on a single factor among cancer patients which dominates all the others in terms of either the risk of developing cancer or the probability of responding to treatment. Usually, the patients in a research study are each unique, and it is far from clear which of the differences among the patients are actually important in terms of survival. One method is to divide the patients into a number of small groups, trying to achieve homogeneity within a group. However, the more different factors considered in a study, the smaller the groups are which differ from the others in one or more factor. This results in groups that contain a small handful of patients, too few to draw useful conclusions. One alternative is to consider each factor separately, but this method also has drawbacks. Different patient characteristics are often correlated with one another. For example, drinking coffee might be found to correlate with increased cancer risk, but this finding means nothing if it is not taken into account that the patients who drank the most coffee were also more likely to smoke cigarettes. The Cox proportional hazards model is a statistical method for taking the various factors which correlate with cancer risk, response to treatment, or any other facet of patient outcome, and teasing out the factors which directly affect the risk, or "hazard" in the actuary's parlance, from the factors which are correlated with the risk factors but do not themselves exert a significant influence on the outcome. (Consumer Summary produced by Reliance Medical Information, Inc.)

Research, Methods, Cancer research, Medical research, Cancer, Medical statistics

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The impact of pulmonary infections on the survival of lung cancer patients

Article Abstract:

The effect of lung infections on survival was assessed in 121 patients with lung cancer. Among 77 men and 44 women in the group, 118 were black and the average age was 63.5 years. The patients were classified according to the type of lung cell affected, which included 43 patients with squamous cell carcinoma, 31 patients with adenocarcinoma, 18 patients with large cell carcinoma, 19 patients with small cell carcinoma, and 10 patients with unclassified lung cancer. The patients were also grouped according to the stage of disease progression which ranged from the early and less advanced phase, Stage 0, to the more advanced, late phase of lung cancer, Stage IV. Two patients were in Stage 0, 15 in Stage I, seven in Stage II, 45 in Stage III, 44 in Stage IV, and eight patients could not be classified according to stage at diagnosis. Among 85 patients with pulmonary infections, 37 had only one infection, and 48 experienced more than one period of infection. The most common infecting microorganisms included alpha/gamma streptococci, Staphylococcus aureus, Klebsiella pneumoniae, Enterobacter aerogenes, Pseudomonas aeruginosa. Patients with infections survived about four months compared with patients without infections who survived an average of almost 13 months. Among patients with Stage III lung cancer, those with infections survived almost six months compared with patients without infections who survived approximately 13 months. These findings show that infections commonly occur in patients with lung cancer and may adversely affect the survival of these patients. (Consumer Summary produced by Reliance Medical Information, Inc.)

Infection, Complications and side effects, Prognosis, Lungs, Lung, Lung cancer

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