Literature DB >> 1662739

Evaluation of nonlinear optimization for scheduling of follow-up cystoscopies to detect recurrent bladder cancer. The Bladder Cancer follow-up Group.

D L Kent1, R A Nease, H C Sox, L D Shortliffe, R Shachter.   

Abstract

Standard recommendations for patients who have had superficial bladder cancer are inspection 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 alternative 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 intervals 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 less than 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 understanding of the accuracy of predictive models for bladder-cancer recurrence rates is desirable. Subsequently, the optimization method developed here may be tested prospectively.

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Year:  1991        PMID: 1662739     DOI: 10.1177/0272989X9101100402

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  7 in total

1.  The role of patients and providers in the timing of follow-up visits. Telephone Care Study Group.

Authors:  H G Welch; M K Chapko; K E James; L M Schwartz; S Woloshin
Journal:  J Gen Intern Med       Date:  1999-04       Impact factor: 5.128

2.  A computerized intervention to improve timing of outpatient follow-up: a multicenter randomized trial in patients treated with warfarin. National Consortium of Anticoagulation Clinics.

Authors:  S D Fihn; M B McDonell; D Vermes; J G Henikoff; D C Martin; C M Callahan; D L Kent; R H White
Journal:  J Gen Intern Med       Date:  1994-03       Impact factor: 5.128

3.  Setting the revisit interval in primary care.

Authors:  L M Schwartz; S Woloshin; J H Wasson; R A Renfrew; H G Welch
Journal:  J Gen Intern Med       Date:  1999-04       Impact factor: 5.128

4.  Routine use of ultrasound and flexible cystoscopy in the control of benign bladder tumours.

Authors:  N O Knoblauch; H Rønning; P Knudsen; L Lund; K T Nielsen
Journal:  Int Urol Nephrol       Date:  1994       Impact factor: 2.370

5.  Cost-effectiveness of surveillance schedules in older adults with non-muscle-invasive bladder cancer.

Authors:  Eveline A M Heijnsdijk; Daan Nieboer; Tullika Garg; Iris Lansdorp-Vogelaar; Harry J de Koning; Matthew E Nielsen
Journal:  BJU Int       Date:  2018-08-27       Impact factor: 5.588

6.  Development and Validation of a Decision Analytical Model for Posttreatment Surveillance for Patients With Oropharyngeal Carcinoma.

Authors:  Vivek Nair; Samuel Auger; Sara Kochanny; Frederick M Howard; Daniel Ginat; Olga Pasternak-Wise; Aditya Juloori; Matthew Koshy; Evgeny Izumchenko; Nishant Agrawal; Ari Rosenberg; Everett E Vokes; M Reza Skandari; Alexander T Pearson
Journal:  JAMA Netw Open       Date:  2022-04-01

7.  Toward cost-effective staffing mixes for Veterans Affairs substance use disorder treatment programs.

Authors:  Jinwoo J Im; Ross D Shachter; John W Finney; Jodie A Trafton
Journal:  BMC Health Serv Res       Date:  2015-11-23       Impact factor: 2.655

  7 in total

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