PubMed Health⌕ Search

Biomedical subjects

P C Prorok

Publications and source records attributed to P C Prorok.

6 recordsLinked to original sources
PubMed1992

Epidemiologic approach for cancer screening. Problems in design and analysis of trials.

The goal of cancer screening is early detection and treatment of disease with a consequent reduction in mortality. The difficult task of evaluating whether a particular screening program can achieve this goal is the theme of this article. Our focus is on the two principal components of the screening process. The first component is the ability of the screening test to detect cancer early, while minimizing the number of false positive results. In this regard, the specificity of the test ordinarily must be very high, approaching 99%. The second component in the screening process is evaluating the overall impact of a screening program. For this, various study designs have been proposed. The best procedure, the randomized controlled trial, is discussed in detail, but alternative designs are also considered. The endpoint in any such study should be cancer-specific mortality. The problems inherent in other outcome variables, such as stage shift and increased length of survival due to lead time and length biases are addressed. Also considered are major difficulties in study design and evaluation, such as inadequate knowledge of the natural history of the disease, particularly of preclinical lesions. Key data items that should be collected for evaluation are listed.

Bias↗
PubMed1991

The case-control design and the assessment of the efficacy of cancer screening.

Case-control studies have been used in recent years to evaluate the efficacy of cancer screening. However, relatively little work has been done to examine the methodology itself for this purpose. In this paper, it is demonstrated that because of self-selection bias the case-control study can yield a biased estimate of screening efficacy. Further, it is shown how this bias can be assessed using data from a randomized trial. Using data from the HIP breast cancer screening study, the magnitude of the self-selection bias is estimated and is seen to be substantial.

Breast Neoplasms↗
PubMed1990

Prospective evaluation of serum CA 125 levels in a normal population, phase I: the specificities of single and serial determinations in testing for ovarian cancer.

To determine the potential efficacy of the CA 125 assay as one component of a strategy for early detection of ovarian malignancy, serum CA 125 levels were determined in 1082 women 40 years of age or older in Stockholm. Initial serum CA 125 levels exceeded 35 U/ml in 36 women (3.3%) and 65 U/ml in 11 women (1.0%), placing the exact 95% upper confidence limits on false positive rates for a single screen at 4.3 and 1.7%, respectively. Follow-up CA 125 levels were obtained for those women with initially elevated levels and a group of age-matched controls. Mean CA 125 levels declined significantly for women with initially elevated levels (P = 0.0014). Interindividual variation and variation within individual subjects over the entire follow-up period were 52 and 35%, respectively. Of the 36 subjects with initially elevated serum CA 125 levels, only 2 showed a doubling of these levels; in only 1 of these 2 was this increase sustained. Intensive clinical follow-up with pelvic examination and ultrasonography, with investigators blinded to CA 125 results, led to the diagnosis of Stage III ovarian cancer in the latter individual. Diagnosis was made 21 months after the initially elevated serum CA 125 measurement and 15 months after the first measured doubling of that level. Because no other malignancies were identified at entry or during the follow-up period (median 560 days) in the women with elevated CA 125 levels, the specificity of the assay over that time period would have been 99.9% using the doubling of an initially elevated value as the criterion for determining positivity and 100% using as the criterion a sustained increase in level for those with initially elevated levels that doubled. These results support the continued investigation of longitudinally collected CA 125 levels to identify individuals at high risk for ovarian malignancy.

Adult↗
PubMed1990

Statistical considerations in cancer screening programs.

The goal of cancer screening is the early detection and treatment of disease, with a consequent reduction in the mortality rate. Evaluation of whether a particular screening program can achieve this goal is a difficult task. Two components of the screening process must be assessed. The first is the ability of the screening test to detect cancer early while minimizing the number of false-positive results. In this regard, the specificity of the test ordinarily must be very high, approaching 99%. No screening test for prostate cancer has yet been reported to have a specificity this high, indicating that any prostate cancer screening program using currently available tests will have to deal with the problem of a large number of false-positive findings. To evaluate the overall impact of a screening program, the best procedure is the randomized controlled trial with cancer-specific mortality as the endpoint. This endpoint is used because it avoids the lead time and length biases inherent in other outcome variables such as stage shift and case survival. The screening randomized controlled trial must be carefully planned and implemented, because it is lengthier and more costly than the usual therapy trial because of differences in study populations, trial design relative to the planned population intervention, and the extent of knowledge of disease natural history. A further important component of screening evaluation is cost. The decision to implement or continue a screening program can be aided by using cost-effectiveness analysis, which bases a decision on the ranking of cost-to-benefit ratios for the various programs contending for limited funds. Screening cost includes the cost of the test, the cost of side effects of the test, and the costs of biopsy and treatment, while screening benefit can be measured in terms of lives saved, life years saved, or quality-adjusted life years.

Cost-Benefit Analysis↗