Dataset Information

Validation study of a web-based assessment of functional recovery after radical prostatectomy.

ABSTRACT:

Background

Good clinical care of prostate cancer patients after radical prostatectomy depends on careful assessment of post-operative morbidities, yet physicians do not always judge patient symptoms accurately. Logistical problems associated with using paper questionnaire limit their use in the clinic. We have implemented a web-interface ("STAR") for patient-reported outcomes after radical prostatectomy.

Methods

We analyzed data on the first 9 months of clinical implementation to evaluate the validity of the STAR questionnaire to assess functional outcomes following radical prostatectomy. We assessed response rate, internal consistency within domains, and the association between survey responses and known predictors of sexual and urinary function, including age, time from surgery, nerve sparing status and co-morbidities.

Results

Of 1581 men sent an invitation to complete the instrument online, 1235 responded for a response rate of 78%. Cronbach's alpha was 0.84, 0.86 and 0.97 for bowel, urinary and sexual function respectively. All known predictors of sexual and urinary function were significantly associated with survey responses in the hypothesized direction.

Conclusions

We have found that web-based assessment of functional recovery after radical prostatectomy is practical and feasible. The instrument demonstrated excellent psychometric properties, suggested that validity is maintained when questions are transferred from paper to electronic format and when patients give responses that they know will be seen by their doctor and added to their clinic record. As such, our system allows ready implementation of patient-reported outcomes into routine clinical practice.

SUBMITTER: Vickers AJ

PROVIDER: S-EPMC2927505 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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Publications

Validation study of a web-based assessment of functional recovery after radical prostatectomy.

Vickers Andrew J AJ Savage Caroline J CJ Shouery Marwan M Eastham James A JA Scardino Peter T PT Basch Ethan M EM

Health and quality of life outcomes 20100805

<h4>Background</h4>Good clinical care of prostate cancer patients after radical prostatectomy depends on careful assessment of post-operative morbidities, yet physicians do not always judge patient symptoms accurately. Logistical problems associated with using paper questionnaire limit their use in the clinic. We have implemented a web-interface ("STAR") for patient-reported outcomes after radical prostatectomy.<h4>Methods</h4>We analyzed data on the first 9 months of clinical implementation to ...[more]

PMID: 20687938

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Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.

Dataset Information

Validation study of a web-based assessment of functional recovery after radical prostatectomy.

Background

Methods

Results

Conclusions

Publications

Validation study of a web-based assessment of functional recovery after radical prostatectomy.

Similar Datasets

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