The goal of screening tests for a chronic disease such as cancer is early detection and treatment with a consequent reduction in mortality from the disease. Screening tests, however, might produce false positive and false-negative results. With an increasing number of screening tests, it is clear that the risk of a false-positive screen, a finding with potentially significant emotional, financial, and health costs, also increases. Elmore et al. (1998, New England Journal of Medicine 338, 1089-1096), Christiansen et al. (2000, Journal of the National Cancer Institute 92, 1657-1666), and Gelfand and Wang (2000, Statistics in Medicine 19, 1865-1879) investigated this problem under the somewhat unrealistic assumption that the choice of making the decision to drop out at the kth screen does not depend upon the results of the earlier k - 1 screens. In this article we obtain sufficient and necessary conditions for their assumption to hold and use one of them to provide a method for testing the validity of the assumption. A new model which does not depend on their assumption is introduced. The maximum likelihood estimator of the cumulative risk of receiving a false-positive screen under the new model is derived and its asymptotic normality is proved. The extension of the new model by incorporating covariate information is also considered. We apply our testing method and the new model to data from the breast cancer screening trial of the Health Insurance Plan of Greater New York.
In studying the relationship between the size of primary cancers and the occurrence of metastases, two quantities are of prime importance. The first is the distribution of tumor size at the point of metastatic transition, while the second is the probability that detectable metastases are present when cancer comes to medical attention. Kimmel and Flehinger (1991, Biometrics 47, 987-1004) developed a general nonparametric model and studied its two limiting cases. Because of unidentifiablity of their general model, a new identifiable model is introduced by making the hazard function for detecting a metastatic cancer a constant. The new model includes Kimmel and Flehinger's (1991) second limiting model as a special case. An estimator of the tumor size distribution at metastases is proposed. The result is applied to a set of colorectal cancer data.
Postoperative pelvic pain is a complication associated with the use of first generation endometrial ablative techniques for treatment of dysfunctional uterine bleeding. This complication usually presents a few months after surgery with a reported incidence ranging from 4.7% to 13.5%. Short-term studies have shown that microwave endometrial ablation (MEA), a second generation endometrial ablation technique, is effective in 70% to 80% of women and has low overall risk of complications. There is, however, no long-term efficacy or safety data. This retrospective, observational study assessed whether hysteroscopic adhesiolysis after MEA could avoid the need for hysterectomy or major surgery in patients with a history of pelvic pain after MEA who were at high risk of intrauterine adhesions.Among the 20 patients in the study population, 17 (85%) were found to have intrauterine adhesions at hysteroscopy that were divided. The cure rate in the group of women with no pelvic pain before the MEA procedure who received hysteroscopic adhesiolysis alone was 85.7% (6/7), whereas only 10% (1/10) of women with pain before MEA were cured with hysteroscopic adhesiolysis alone (P Ͻ 0.01). At follow-up, 45% (9/20) of patients had been cured of pain by hysteroscopic adhesiolysis and were discharged. Of the 55% (11/20) patients with lingering complaints of pain, 9 underwent hysterectomy, 1 who was found to have endometriosis at laparoscopy had a laparoscopic bilateral salpingooophorectomy, and 1 received mefenamic acid. No serious adverse reactions were noted with hysteroscopic adhesiolysis.These findings suggest that hysteroscopic adhesiolysis is beneficial for patients with no history of pain before the MEA procedure. As a result, hysterectomy can be avoided in such patients who in this study comprised nearly half of the study population. The small number of cases limits the study. GYNECOLOGYVolume 64, Number 9 OBSTETRICAL AND GYNECOLOGICAL SURVEY ABSTRACTVaginal vault dehiscence, a surgical emergency, is a rare complication of hysterectomy that can occur a few weeks, several months, or years after the operation. Its incidence in several studies ranged from 0.03% to 0.3%. There is relatively little detailed information on predisposing factors for vault dehiscence and its manifestation after hysterectomy. This retrospective case series and literature review evaluated factors predisposing to vault dehiscence after hysterectomy and its manifestation. A total of 54 cases of vault dehiscence were identified: 16 were unpublished cases of vaginal vault dehiscence after total laparoscopic hysterectomy obtained from 5 physicians participating in the American Association of Gynecologic Laparoscopists Endo Exchange List (group A) and 38 cases were found in an English-language literature search (group B). Participating physicians completed a detailed questionnaire containing demographic data, indications and type of hysterectomy, operative procedure, predisposing factors, and potential triggering factors for dehiscence. The literature search was ...
The goal of screening programmes for cancer is early detection and treatment with a consequent reduction in mortality from the disease. Screening programmes need to assess the true benefit of screening, that is, the length of time of extension of survival beyond the time of advancement of diagnosis (lead-time). This paper presents a non-parametric method to estimate the survival function of the post-lead-time survival (or extra survival time) of screen-detected cancer cases based on the observed total life time, namely, the sum of the lead-time and the extra survival time. We apply the method to the well-known data set of the HIP (Health Insurance Plan of Greater New York) breast cancer screening study. We make comparisons with the survival of other groups of cancer cases not detected by screening such as interval cases, cases among individuals who refused screening, and randomized control cases. As compared with Walter and Stitt's model, in which they made parametric assumptions for the extra survival time, our non-parametric method provides a better fit to HIP data in the sense that our estimator for the total survival time has a smaller sum of squares of residuals.
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