Prognostic value of various morphometric measurements of tumour extent in prostate needle core tissue.

AIMS: Predicting prostatic cancer patients' outcome is a major objective for clinicians and patients. Several nomograms are currently implemented prior to treatment to help predict clinical and pathological outcome. The aim of this study was to investigate the prognostic significance of morphometric measurements of cancer on the needle biopsy specimen in relation to the final pathological stage or the biochemical failure status following radical prostatectomy, and to determine which measurement of tumour length in cases with discontinuous foci of cancer (DFC) is most reliably reflective of the pathological stage. METHODS AND RESULTS: Of the 100 patients included in this study, 34% had high-stage disease (pT >or= 3 and/or pN1) and 16% experienced biochemical recurrence. The analysis showed that fraction of positive cores, total percentage of cancer and both total and greatest millimetric cancer lengths were the variables most closely associated with pathological stage and biochemical failure status. CONCLUSIONS: This study confirms the prognostic value of recording tumour extent in prostatic needle biopsy reporting. However, the results are inconclusive in determining the best method to record tumour length in cores with DFC and larger studies are needed to answer this question fully.

Validation study of the LAMBDA model for predicting the BRCA1 or BRCA2 mutation carrier status of North American Ashkenazi Jewish women.

LAMBDA is a model that estimates the probability an Ashkenazi Jewish (AJ) woman carries an ancestral BRCA1 or BRCA2 mutation from her personal and family cancer history. LAMBDA is relevant to clinical practice, and its implementation does not require a computer. It was developed principally from Australian and UK data. We conducted a validation study using 1286 North American AJ women tested for the mutations 185delAG and 5382insC in BRCA1 and 6174delT in BRCA2. Most had a personal or family history of breast cancer. We observed 197 carriers. The area under the receiver operator characteristic (ROC) curve (a measure of ranking) was 0.79 [95% confidence interval (CI) = 0.77-0.81], similar to that for the model-generating data (0.78; 95% CI = 0.75-0.82). LAMBDA predicted 232 carriers (18% more than observed; p = 0.002) and was overdispersed (p = 0.009). The Bayesian computer program BRCAPRO gave a similar area under the ROC curve (0.78; 95% CI = 0.76-0.80), but predicted 367 carriers (86% more than observed; p < 0.0001), and was substantially overdispersed (p < 0.0001). Therefore, LAMBDA is comparable to BRCAPRO for ranking AJ women according to their probability of being a BRCA1 or BRCA2 mutation carrier and is more accurate than brcapro which substantially overpredicts carriers in this population.