Biomedical subjects

R Guy Hudson

Publications and source records attributed to R Guy Hudson.

3 recordsLinked to original sources

PubMed2005

Improved detection of prostate cancer using classification and regression tree analysis.

PURPOSE: To build a decision tree for patients suspected of having prostate cancer using classification and regression tree (CART) analysis. PATIENTS AND METHODS: Data were uniformly collected on 1,433 referred men with a serum prostate-specific antigen (PSA) levels of < or = 10 ng/mL who underwent a prostate biopsy. Factors analyzed included demographic, laboratory, and ultrasound data (ie, hypoechoic lesions and PSA density [PSAD]). Twenty percent of the data was randomly selected and reserved for study validation. CART analysis was performed in two steps, initially using PSA and digital rectal examination (DRE) alone and subsequently using the remaining variables. RESULTS: CART analysis selected a PSA cutoff of more than 1.55 ng/mL for further work-up, regardless of DRE findings. CART then selected the following subgroups at risk for a positive biopsy: (1) PSAD more than 0.165 ng/mL/cc; (2) PSAD < or = 0.165 ng/mL/cc and a hypoechoic lesion; (3) PSAD < or = 0.165 ng/mL/cc, no hypoechoic lesions, age older than 55.5 years, and prostate volume < or = 44.0 cc; and (4) PSAD < or = 0.165 ng/mL/cc, no hypoechoic lesions, age older than 55.5 years, and 50.25 cc less than prostate volume < or = 80.8 cc. In the validation data set, specificity and sensitivity were 31.3% and 96.6%, respectively. Cancers that were missed by the CART were Gleason score 6 or less in 93.4% of cases. Receiver operator characteristic curve analysis showed that CART and logistic regression models had similar accuracy (area under the curve = 0.74 v 0.72, respectively). CONCLUSION: Application of CART analysis to the prostate biopsy decision results in a significant reduction in unnecessary biopsies while retaining a high degree of sensitivity when compared with the standard of performing a biopsy of all patients with an abnormal PSA or DRE.

Adult↗

PubMed2005

Ureteric access with flexible ureteroscopes: effect of the size of the ureteroscope.

OBJECTIVE: To determine the optimum size of a flexible ureteroscope (FU) to minimize the need for ureteric dilatation. MATERIALS AND METHODS: FUs from several different manufacturers and with different shaft diameters were used for ureteroscopy in adults. An initial attempt was made to pass one of the larger diameter FUs; if this was unsuccessful, the smaller 7.5 F FU was used. The results were reviewed retrospectively. RESULTS: Flexible ureteroscopy was used in 115 consecutive patients at two different institutions. The ability to pass the FUs with no formal dilatation was directly related to the FU diameter. The rate of failing to pass with no formal dilatation was 37% for the 9.0 F, 8.5% for the 8.6 F, 5% for the 8.4 F and 0.9% for the 7.4 F ureteroscope. CONCLUSION: Although other factors influence the overall effectiveness of the FU, the ability to pass FUs is directly related to their outer diameter. When only the ease of introduction is considered, the ideal ureteroscope outer diameter is 7.4 F.

Adult↗

PubMed2003

Predictive modeling for the presence of prostate carcinoma using clinical, laboratory, and ultrasound parameters in patients with prostate specific antigen levels < or = 10 ng/mL.

BACKGROUND: The objective of the current study was to develop a model for predicting the presence of prostate carcinoma using clinical, laboratory, and transrectal ultrasound (TRUS) data. METHODS: Data were collected on 1237 referred men with serum prostate specific antigen (PSA) levels < or = 10 ng/mL who underwent an initial prostate biopsy. Variables analyzed included age, race, family history, referral indication(s), prior vasectomy, digital rectal examination (DRE), PSA level, PSA density (PSAD), and TRUS findings. Twenty percent of the data were reserved randomly for study validation. Logistic regression analysis was performed to estimate the relative risk, 95% confidence interval, and P values. RESULTS: Independent predictors of a positive biopsy result included elevated PSAD, abnormal DRE, hypoechoic TRUS finding, and age 75 years or older. Based on these variables, a predictive nomogram was developed. The sensitivity and specificity of the model were 92% and 24%, respectively, in the validation study for which the predictive probability > or = 10% was used to indicate the presence of prostate carcinoma. The area under the receiver operating characteristic curve (AUC) for the model was 73%, which was significantly higher compared with the prediction based on PSA alone (AUC, 62%). If it was validated externally, then application of this model to the biopsy decision could result in a 24% reduction in unnecessary biopsy procedures, with an overall reduction of 20%. CONCLUSIONS: Incorporation of clinical, laboratory, and TRUS data into a prebiopsy nomogram significantly improved the prediction of prostate carcinoma over the use of individual factors alone. Predictive nomograms may serve as an aid to patient counseling regarding prostate biopsy outcome and to reduce the number of unnecessary biopsy procedures.

Adenocarcinoma↗