A Nomogram to Predict Seminal Vesicle Invasion by the Extent and Location of Cancer in Systematic Biopsy Results
Department of Urology, Memorial Sloan-Kettering Cancer Institute, New York, New York, USA. The Journal of Urology
(Impact Factor: 4.47).
10/2003; 170(4 Pt 1):1203-8. DOI: 10.1097/01.ju.0000085074.62960.7b
We determined whether systematic biopsy results increases the accuracy of standard clinical information in predicting seminal vesicle invasion (SVI).
We analyzed a retrospective cohort of 763 patients with clinical stages T1c-T3 prostate cancer who were diagnosed by systematic biopsy and treated with radical prostatectomy. We recorded the location of each biopsy core and measured the length of cancer and total length of each core. Using logistic regression analysis we constructed and internally validated a nomogram to predict SVI.
A total of 60 patients (7.9%) had SVI. Cancer was present in a biopsy core from the base in 437 patients, of whom 12.8% had SVI compared with only 1.2% of the 326 without cancer at the base. None of the 275 patients with prostate specific antigen (PSA) 10 ng/ml or less and no cancer at the base had SVI. On multivariate analysis serum PSA (p <0.0005), primary Gleason grade (p = 0.028) and percent cancer at the base (p <0.005) were the only significant predictors of SVI. The predictive accuracy of a standard model that included only stage, grade and PSA was maximally enhanced by including the percent cancer at the base (p = 0.0013). A nomogram that incorporated this variable produced probabilities of SVI that differed from the standard model by +/- 10% in 68% of the cases.
The presence and amount of cancer in systematic needle biopsy cores from the base of the prostate strongly predicts the presence of SVI. Systematic biopsy results enhance the accuracy of nomograms to predict SVI.
Available from: Felix KH Chun
- "Tools that were developed in a different era may not provide equally accurate predictions in contemporary patients. For example , nomograms that are based on systematic sextant biopsy information should be updated according to the current gold standard, namely, extended biopsy schemes . (3) Finally, the predicted outcome of interest needs to be put in perspective. "
[Show abstract] [Hide abstract]
ABSTRACT: Several nomograms have been developed to predict outcomes related to prostate cancer (PCa).
We provide a descriptive and an analytic comparison of nomograms. Further, we report a set of recent PCa nomograms, in which we recorded predictor variables, number of patients used to develop each nomogram, and nomogram-specific features. Moreover, accuracy estimates and type of validation are considered.
Our findings suggest a demand for updated nomograms in selected fields of PCa outcomes. Moreover, an increasing number of nomograms address important end points such as prostate-specific antigen recurrence, distant metastases, or androgen-independent PCa-specific survival.
Our results suggest that nomograms are available for many PCa-related outcomes. They represent a valid methodologic approach if correct criteria are met.
European Urology 12/2006; 50(5):914-26; discussion 926. DOI:10.1016/j.eururo.2006.07.042 · 13.94 Impact Factor
Available from: Harald Kittler
- "Although programmable calculators and personal digital assistants (PDAs) have begun to allow the storage of models in digital form, nomographic representations of logistic regression models are still popular as decision support tools in many areas of clinical medicine           . "
[Show abstract] [Hide abstract]
ABSTRACT: Logistic regression models are widely used in medicine, but difficult to apply without the aid of electronic devices. In this paper, we present a novel approach to represent logistic regression models as nomograms that can be evaluated by simple line drawings. As a case study, we show how data obtained from a questionnaire-based patient self-assessment study on the risks of developing melanoma can be used to first identify a subset of significant covariates, build a logistic regression model, and finally transform the model to a graphical format. The advantage of the nomogram is that it can easily be mass-produced, distributed and evaluated, while providing the same information as the logistic regression model it represents.
Journal of Biomedical Informatics 11/2005; 38(5):389-94. DOI:10.1016/j.jbi.2005.02.006 · 2.19 Impact Factor
Available from: Katia Leite
[Show abstract] [Hide abstract]
ABSTRACT: To determine through preoperative serum PSA level, Gleason score on biopsy and percentage of fragments affected by tumor on biopsy, the probability of involvement of the seminal vesicles.
During the period between March 1991 to December 2002, we selected 899 patients undergoing radical prostatectomy for treatment of localized prostate adenocarcinoma. The analyzed preoperative variables were PSA, percentage of positive fragments and Gleason score on the biopsy. Pre-operative PSA was divided in scales from 0 to 4.0 ng/mL, 4.1 to 10 ng/mL, 10.1 to 20 ng/mL and > 20 ng/mL, Gleason score was categorized in scales from 2 to 6. 7 and 8 to 10, and the percentage of affected fragments was divided in 0 to 25%, 25.1% to 50%, 50.1% to 75%, and 75.1% to 100%. All these variables were correlated with the involvement of seminal vesicles in the surgical specimen.
Of the 899 patients under study, approximately 11% (95% CI, [9% - 13%]) had involvement of seminal vesicles. On the multivariate analysis, when PSA was < or = 4, the Gleason score was 2 to 6, and less than 25% of fragments were involved on the biopsy, only 3.6%, 7.6% and 6.2% of patients respectively, had involvement of seminal vesicles. On the multivariate analysis, we observed that PSA, Gleason score and the percentage of involved fragments were independent prognostic factors for invasion of seminal vesicles.
The preoperative variables used in the present study allow the identification of men with minimal risk (lower than 5%) if involvement of seminal vesicles.
International braz j urol 01/2004; 30(6):472-8. DOI:10.1590/S1677-55382004000600004 · 0.88 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.