This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Kent, D. L. Articles by Shachter, R. Search for Related Content PubMed PubMed Citation Articles by Kent, D. L. Articles by Shachter, R. Social Bookmarking                   What's this?

Eualuation of Nonlinear Optimization for Scheduling of follow-up cystoscopies to Detect Recurrent Bladder Cancer

Robert A. Nease, PhD

Harold C. Sox, JR, MD

Linda D. Shortliffe, MD

Ross Shachter, PhD

Standard recommendations for patients who have had superficial bladder cancer are in spection by cystoscopy quarterly for a year or two after tumor removal, then half-yearly and yearly. The authors assessed the potential for improvement in scheduling cystoscopies according to probabilistic optimization techniques. Eight hypothetical practices were created, based on retrospective analysis of 918 bladder-cancer-patient charts. Standard and alter native recommendations for the interval to next cystoscopy were compared. The alternatives were derived from patient-specific predictions of future tumor risks (based on the patient's prior recurrence rate and tumor stage and grade) and a nonlinear optimization approach to allocation of the same number of cystoscopies as were available for standard follow-up. The optimization proposed longer intervals between visits for low-risk patients and shorter inter vals for high-risk patients. Overall, optimization reduced expected tumor detection delays by 30%, from 12.6 to 8.7 weeks. When optimization intervals were shorter than standard, cancer was found more often at subsequent cystoscopies (34% vs 27%, p < 0.05), suggesting that the optimization was a better predictor of cancer recurrence. If reduction in tumor-detection delay is the goal of follow-up for recurrent cancers, then urologists can improve monitoring by using probabilistic optimization methods for scheduling cystoscopies. Further understand ing of the accuracy of predictive models for bladder-cancer recurrence rates is desirable. Subsequently, the optimization method developed here may be tested prospectively. Key words: bladder cancer; nonlinear optimization; operations research; follow-up studies; mon itoring; cystoscopy; health services; decision analysis. (Med Decis Making 1991;11:240- 248)

Medical Decision Making, Vol. 11, No. 4, 240-248 (1991)
DOI: 10.1177/0272989X9101100402


CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?