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PubMed1999

A novel approach to predicting P450 mediated drug metabolism. CYP2D6 catalyzed N-dealkylation reactions and qualitative metabolite predictions using a combined protein and pharmacophore model for CYP2D6.

A combined protein and pharmacophore model for cytochrome P450 2D6 (CYP2D6) has been extended with a second pharmacophore in order to explain CYP2D6 catalyzed N-dealkylation reactions. A group of 14 experimentally verified N-dealkylation reactions form the basis of this second pharmacophore. The combined model can now accommodate both the usual hydroxylation and O-demethylation reactions catalyzed by CYP2D6, as well as the less common N-dealkylation reactions. The combined model now contains 72 metabolic pathways catalyzed by CYP2D6 in 51 substrates. The model was then used to predict the involvement of CYP2D6 in the metabolism of a "test set" of seven compounds. Molecular orbital calculations were used to suggest energetically favorable sites of metabolism, which were then examined using modeling techniques. The combined model correctly predicted 6 of the 8 observed metabolites. For the well-established CYP2D6 metabolic routes, the predictive value of the current combined protein and pharmacophore model is good. Except for the highly unusual metabolism of procainamide and ritonavir, the known metabolites not included in the development of the model were all predicted by the current model. Two possible metabolites have been predicted by the current model, which have not been detected experimentally. In these cases, the model may be able to guide experiments. P450 models, like the one presented here, have wide applications in the drug design process which will contribute to the prediction and elimination of polymorphic metabolism and drug-drug interactions.

1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine↗

PubMed1998

Grade predictions for school-leaving examinations: do they predict anything?

The attributes of 721 medical students admitted to the United Medical and Dental Schools (UMDS) of Guy's and St. Thomas' Hospitals, London, UK between the years 1991 and 1994 were examined to determine the relationship between A-level grade predictions (as completed on each student's UCAS form by their school/college at the time of their application to the school) and subsequent assessments of their academic ability and performance. Predicted A-level grades were found to be significantly, if weakly, correlated with the rating of academic ability made at interview by the UMDS interviewing panel. They were not however, related to the grades obtained by students in the A-level examination itself. Further, while success at pre-clinical examinations was predicted by obtained A-level grades, it showed no relationship with the predicted grades. In contrast, the interview-based rating of the applicant's academic potential was significantly predictive of subsequent A level and, to a lesser extent, pre-clinical examination performance. It is concluded that predicted A-level grades may not offer a valid method of assessing the academic potential of applicants for medical school.

Education, Medical, Undergraduate↗

PubMed2006

Protein structural motif prediction in multidimensional phi-psi space leads to improved secondary structure prediction.

A significant step towards establishing the structure and function of a protein is the prediction of the local conformation of the polypeptide chain. In this article, we present systems for the prediction of three new alphabets of local structural motifs. The motifs are built by applying multidimensional scaling (MDS) and clustering to pair-wise angular distances for multiple phi-psi angle values collected from high-resolution protein structures. The predictive systems, based on ensembles of bidirectional recurrent neural network architectures, and trained on a large non-redundant set of protein structures, achieve 72%, 66%, and 60% correct motif prediction on an independent test set for di-peptides (six classes), tri-peptides (eight classes) and tetra-peptides (14 classes), respectively, 28-30% above baseline statistical predictors. We then build a further system, based on ensembles of two-layered bidirectional recurrent neural networks, to map structural motif predictions into a traditional 3-class (helix, strand, coil) secondary structure. This system achieves 79.5% correct prediction using the "hard" CASP 3-class assignment, and 81.4% with a more lenient assignment, outperforming a sophisticated state-of-the-art predictor (Porter) trained in the same experimental conditions. The structural motif predictor is publicly available at: http://distill.ucd.ie/porter+/.

Amino Acid Motifs↗

PubMed2006

Radiation rescue for biochemical failure after surgery for prostate cancer: predictive parameters and an assessment of contemporary predictive models.

OBJECTIVES: To determine pretreatment prognostic variables that predict outcome of radiotherapy for biochemical failure after prostate cancer surgery and evaluate contemporary clinical decision tools for patient selection. METHODS: Fifty patients were identified with failure after rescue radiation was defined as a confirmed rise in PSA, distant metastases, prostate cancer death, or initiation of hormonal therapy. Univariate analysis and multivariate Cox models were constructed. Outcome was compared with decision tree and recursive partitioning predictive models. RESULTS: The median preradiation PSA (pre-RT PSA) was 1.2 ng/mL and the median dose of radiation was 66.6 Gy; median follow-up was 39.6 months. Overall, the estimated 3-year failure free survival was 54%, 95%CI [43,74]. Seminal vesicle involvement (SVI) (P = 0.003) and preradiation PSA Doubling Time (PSADT) <10 months (P = 0.01) were both significant predictors for treatment failure whereas pre-RT PSA was of borderline significance (P = 0.07). On multivariate analysis a pre-RT PSA of >1 and SVI were associated with hazard ratios of 6.2 and 7.3 (P = 0.01 and P = 0.004), respectively. An additional Cox model constructed for 31 patients for whom pre-RT PSADT could be calculated showed PSADT and SVI to be independent prognostic parameters. Two predictive models, a decision tree analysis, and a recursive partitioning model were moderately accurate in predicting outcome in this series, however, high-risk patients experienced less treatment failures than predicted. CONCLUSIONS: Pre-RT PSA <1 ng/mL, longer PSADT (>10 months) and no SVI are associated with improved outcome after rescue radiation. Contemporary clinical prediction tools are imperfect predictors of outcome for rescue radiation therapy.

Decision Trees↗

PubMed2006

Early prediction of mortality in isolated head injury patients: a new predictive model.

BACKGROUND: To construct a predictive model of survival in isolated head injury patients, on the basis of easily available parameters that are independent risk factors for survival outcome. METHODS: Trauma registry-based study of head injury patients who had no other major extracranial injuries and were not hypotensive at admission. A predictive model of probability of death was constructed using discriminant analysis, on the basis of admission Glasgow Coma Scale (GCS) score, head Abbreviated Injury Score (AIS), age, and mechanism of injury. RESULTS: The study included 7,191 patients with head trauma. The overall correct classification rate of the proposed predictive model was 94.2% as compared with 89.0% of the admission GCS score (p < 0.05) and 92.8% of the head AIS (p < 0.05). The correct classification rate of the predictive model developed for the severe head trauma (GCS score 4-8) patients was 79.9%, as compared with 72.6% using the admission GCS score alone or 75.1% (p < 0.05). A one-page, easy to use table summarizing the predicted mortality on the basis of GCS score, head AIS, mechanism of injury, and age was developed. CONCLUSIONS: The proposed model has a significantly better predictive power, especially in severe head trauma, than the extensively used GCS and head AIS. A simple table on the probability of death of a particular patient based on admission GCS score, head AIS, mechanism of injury and age of patient can provide instant information.

Abbreviated Injury Scale↗

PubMed2006

Maturity of judgement in decision making for predictive testing for nontreatable adult-onset neurogenetic conditions: a case against predictive testing of minors.

International guidelines developed to minimize harm from predictive testing for adult-onset, nontreatable neurogenetic conditions such as Huntington disease (HD) state that such testing should not be available to minors. Some authors have proposed that predictive testing for these conditions should be available to minors at the request of parents and/or of younger adolescents themselves. They highlight the lack of empirical evidence that predictive testing of minors causes harm and suggest that refusing to test minors may be detrimental. The current study focuses on the context of predictive test requests by adolescents younger than 18 years, and presents arguments and evidence that the risk of potential harm from testing such young people is sufficiently high to justify continued caution in this area. A study based on a model of psychosocial maturity found that the 3 factors involved in maturity of judgement in decision making - responsibility, temperance and perspective - continue to develop into late adolescence. There is also evidence that the prefrontal areas of the brain, which are involved in executive functions such as decision making, are not fully developed until early adulthood. Combined with evidence of adverse long-term effects, from research with adults who have undergone predictive testing, these findings constitute grounds for retaining a minimum age of 18 years for predictive testing for nontreatable conditions. Further research on assessment of maturity will assist with reaching a consensus on this issue.

Adolescent↗

PubMed1998

Predicting operative risk for coronary artery surgery in the United Kingdom: a comparison of various risk prediction algorithms.

OBJECTIVE: To compare the ability of four risk models to predict operative mortality after coronary artery bypass graft surgery (CABG) in the United Kingdom. DESIGN: Prospective study. SETTING: Two cardiothoracic centres in the United Kingdom. SUBJECTS: 1774 patients having CABG. MAIN OUTCOME MEASURES: Risk factors were recorded for all patients, along with in-hospital mortality. Predicted mortality was derived from the American Society of Thoracic Surgeons (STS) risk program, Ontario Province risk score (PACCN), Parsonnet score, and the UK Society of Cardiothoracic Surgeons risk algorithm. RESULTS: There were significant differences (p < 0.05) between the British and American populations from which the STS risk algorithm was derived with respect to most variables. The observed mortality in the British population was 3.7% (65 of 1774). The mean predicted mortality by STS score, PACCN, Parsonnet score, and UK algorithms were 1.1%, 1.6%, 4.6%, and 4.7% respectively. The overall predictive ability of the models as measured by the area under the receiver operating characteristic curve were 0.64, 0.60, 0.73, and 0.75, respectively. CONCLUSIONS: There are differences between the British and American populations for CABG and the North American algorithms are not useful for predicting mortality in the United Kingdom. The UK Society of Cardiothoracic Surgeons algorithm is the best of the models tested but still only has limited predictive ability. Great care must be exercised when using methods of this type for comparisons of units and surgeons.

Aged↗

PubMed1996

Prediction of psychological functioning one year after the predictive test for Huntington's disease and impact of the test result on reproductive decision making.

For people at risk for Huntington's disease, the anxiety and uncertainty about the future may be very burdensome and may be an obstacle to personal decision making about important life issues, for example, procreation. For some at risk persons, this situation is the reason for requesting predictive DNA testing. The aim of this paper is two-fold. First, we want to evaluate whether knowing one's carrier status reduces anxiety and uncertainty and whether it facilitates decision making about procreation. Second, we endeavour to identify pretest predictors of psychological adaptation one year after the predictive test (psychometric evaluation of general anxiety, depression level, and ego strength). The impact of the predictive test result was assessed in 53 subjects tested, using pre- and post-test psychometric measurement and self-report data of follow up interviews. Mean anxiety and depression levels were significantly decreased one year after a good test result; there was no significant change in the case of a bad test result. The mean personality profile, including ego strength, remained unchanged one year after the test. The study further shows that the test result had a definite impact on reproductive decision making. Stepwise multiple regression analyses were used to select the best predictors of the subject's post-test reactions. The results indicate that a careful evaluation of pretest ego strength, depression level, and coping strategies may be helpful in predicting post-test reactions, independently of the carrier status. Test result (carrier/ non-carrier), gender, and age did not significantly contribute to the prediction. About one third of the variance of post-test anxiety and depression level and more than half of the variance of ego strength was explained, implying that other psychological or social aspects should also be taken into account when predicting individual post-test reactions.

Adult↗

PubMed2006

Dissociable systems for gain- and loss-related value predictions and errors of prediction in the human brain.

Midbrain dopaminergic neurons projecting to the ventral striatum code for reward magnitude and probability during reward anticipation and then indicate the difference between actual and predicted outcome. It has been questioned whether such a common system for the prediction and evaluation of reward exists in humans. Using functional magnetic resonance imaging and a guessing task in two large cohorts, we are able to confirm ventral striatal responses coding both reward probability and magnitude during anticipation, permitting the local computation of expected value (EV). However, the ventral striatum only represented the gain-related part of EV (EV+). At reward delivery, the same area shows a reward probability and magnitude-dependent prediction error signal, best modeled as the difference between actual outcome and EV+. In contrast, loss-related expected value (EV-) and the associated prediction error was represented in the amygdala. Thus, the ventral striatum and the amygdala distinctively process the value of a prediction and subsequently compute a prediction error for gains and losses, respectively. Therefore, a homeostatic balance of both systems might be important for generating adequate expectations under uncertainty. Prevalence of either part might render expectations more positive or negative, which could contribute to the pathophysiology of mood disorders like major depression.

Adult↗

PubMed2006

Using simulation models to predict feed intake: phenotypic and genetic relationships between observed and predicted values in cattle.

The objectives of this study were to evaluate the accuracy of the Decision Evaluator for the Cattle Industry (DECI) and the Cornell Value Discovery System (CVDS) in predicting individual DMI and to assess the feasibility of using predicted DMI data in genetic evaluations of cattle. Observed individual animal data on the average daily DMI (OFI), ADG, and carcass measurements were obtained from postweaning records of 504 steers from 52 sires (502 with complete data). The experimental data and daily temperature and wind speed data were used as inputs to predict average daily feed DMI (kg) required (feed required; FR) for maintenance, cold stress, and ADG; maintenance and cold stress; ADG; maintenance and ADG; and maintenance alone, with CVDS (CFRmcg, CFRmc, CFRg, CFRmg, and CFRm, respectively) and DECI (DFRmcg, DFRmc, DFRg, DFRmg, and DFRm, respectively). Genetic parameters were estimated by REML using an animal model with age on test as a covariate and with genotype, age of dam, and year as fixed effects. Regression equations for observed on predicted DMI were OFI = 1.27 (SE = 0.27) + 0.83 (SE = 0.04) x CFRmcg [R2 = 0.44, residual SD (s(y.x)) = 0.669 kg/d] and OFI = 1.32 (SE = 0.22) + 0.8 (SE = 0.03) x DFRmcg (R2 = 0.53, s(y.x) = 0.612 kg/d). Heritability of OFI was 0.27 +/- 0.12, and heritabilities ranged from 0.33 +/- 0.12 to 0.41 +/- 0.13 for predicted measures of DMI. Phenotypic and genetic correlations between OFI and CFRmcg, CFRmc, CFRg, CFRmg, CFRm, DFRmcg, DFRmc, DFRg, DFRmg, and DFRm were 0.67, 0.73, 0.41, 0.63, 0.78, 0.73, 0.82, 0.45, 0.77, and 0.86 (P < 0.001 for all phenotypic correlations); and 0.95 +/- 0.07, 0.82 +/- 0.13, 0.89 +/- 0.09, 0.95 +/- 0.07, 0.91 +/- 0.09, 0.96 +/- 0.07, 0.89 +/- 0.09, 0.88 +/- 0.09, 0.96 +/- 0.06, and 0.96 +/- 0.07, respectively. Phenotypic and genetic correlations between CFRmcg and DFRmcg, CFRmc and DFRmc, CFRg and DFRg, CFRmg and DFRmg, and CFRm and DFRm were 0.98, 0.94, 0.99, 0.98, and 0.95 (P < 0.001 for all phenotypic correlations), and 0.99 +/- 0.004, 0.98 +/- 0.017, 0.99 +/- 0.004, 0.99 +/- 0.005, and 0.97 +/- 0.021, respectively. The strong genetic relationships between OFI and CFRmcg, CFRmg, DFRmcg, and DFRmg indicate that these predicted measures of DMI may be used in genetic evaluations and that DM requirements for cold stress may not be needed, thus reducing model complexity. However, high genetic correlations for final weight with OFI, CFRmcg, and DFRmcg suggest that the technology needs to be further evaluated in populations with genetic variance in feed efficiency.

Animal Feed↗

PubMed1994

Predictive value of Müller maneuver, cephalometry and clinical features for the outcome of uvulopalatopharyngoplasty. Evaluation of predictive factors using discriminant analysis in 30 sleep apnea patients.

The success rate of uvulopalatopharyngoplasty (UPPP) in the treatment of obstructive sleep apnea is generally only 50-60%. In order to improve this, various predictive factors for the outcome of UPPP were studied, including the Müller maneuver and cephalometry. Thirty unselected consecutive patients with obstructive sleep apnea (median apnea index (AI) 26 apneas/h, range 5-78) underwent UPPP with standard tonsillectomy except in the case of small tonsils and using CO2 laser for the palatal resection. Polysomnographic control 5 months after surgery showed that 63% of all patients had obtained a reduction in AI > or = 50% including an AI < 20 after surgery. Tonsillectomy had no influence on the outcome. Further, the Müller maneuver did not predict the outcome, whereas cephalometry proved to be of good predictive value. Lowered position of the hyoid bone, increased cranio-cervical angle and shortening of the maxilla length were significantly associated with poor results of UPPP, as were overweight, narrowing of the hypopharynx, the severity of sleep apnea, and hypersomnia. However, in a discriminant analysis containing all these variables, the three cephalometric measurements together with hypersomnia were most closely associated with the outcome of UPPP. A predictive model containing these four variables could correctly classify 83% of the patients in the present study. The model had a false positive rate of 7% in predicting a successful outcome. This indicates that cephalometry is mandatory in the selection of UPPP candidates and that a predictive model containing some or all of the four variables may substantially improve the success rate.

Adult↗

PubMed1993

The ability of adolescents to predict future outcome. Part II: Therapeutic enhancement of predictive skills.

The assertion of autonomy, a developmental challenge of adolescence, helps predict the teenager's attitude toward pregnancy and parenthood. Significantly, the ability to predict the future relationship with the infant has direct implications for the achievement of an adaptive outcome. Indeed, the interpersonal outcome of the parent-infant relationship may be predicted by the adolescent's behaviors with her infant. A prospective orientation may offer an important vantage point for improving this relationship. For example, the ability to predict future outcome helps identify potential conflict, such as abuse. When applying a prospective approach during the prenatal period, the adolescent's past relationship with her own mother and her motivations for becoming a parent will be explored in order to predict the future dyadic relationship. For adolescents who are already parents, an assessment of the dyad's contemporaneous interaction may further predict future interpersonal exchange. Moreover, orienting the adolescent parent toward the future may identify areas of potential conflict, as well as foster more adaptive dyadic exchange.

Adolescent↗

PubMed2005

Fear of pain, not pain catastrophizing, predicts acute pain intensity, but neither factor predicts tolerance or blood pressure reactivity: an experimental investigation in pain-free individuals.

Previous studies of the Fear-Avoidance Model of Exaggerated Pain Perception have commonly included patients with chronic low back pain, making it difficult to determine which psychological factors led to the development of an "exaggerated pain perception". This study investigated the validity of the Fear-Avoidance Model of Exaggerated Pain Perception by considering the influence of fear of pain and pain catastrophizing on acute pain perception, after considering sex and anxiety. Thirty-two males and 34 females completed the State-Trait Anxiety Inventory, the Fear of Pain Questionnaire, and the Coping Strategies Questionnaire. Subjects underwent a cold pressor procedure and tolerance, pain intensity, and blood pressure reactivity were measured. Sex, anxiety, fear of pain, and pain catastrophizing were simultaneously entered into separate multiple regression models to predict different components of pain perception. Tolerance was not predicted by fear of pain, pain catastrophizing, or anxiety. Pain intensity at threshold and tolerance were significantly predicted by fear of pain, only. Blood pressure reactivity to pain was significantly predicted by anxiety, only. These results suggest that fear of pain may have a stronger influence on acute pain intensity when compared to pain catastrophizing, while neither of the factors predicted tolerance or blood pressure reactivity.

Acute Disease↗

PubMed1999

Validation of a predictive model for asthma admission in children: how accurate is it for predicting admissions?

We studied 364 index presentations to the Emergency Department of a children's hospital with a diagnosis of asthma. The admission rate for this group of children was about 31%. We developed a parsimonious multiple logistic regression model to predict asthma hospital admission based on asthma severity indicators. We then evaluated the model's predictive ability using two methods of cross-validation, using the same sample that was used for the predictive model, and using data from a split sample. The logistic regression model had a predictive accuracy of 90% (95% confidence interval 85-95%). The sensitivity and specificity were 86% and 88%, respectively. Cross-validation models confirmed that the predictive ability of the model was stable. In studies with limited sample sizes, it is possible to validate a model without setting aside a split sample for cross-validation.

Acute Disease↗

PubMed2003

Predictive value of diminutive colonic adenoma trial: the PREDICT trial.

BACKGROUND & AIMS: Diminutive adenomas (1-9 mm in diameter) are frequently found during colon cancer screening with flexible sigmoidoscopy (FS). This trial assessed the predictive value of these diminutive adenomas for advanced adenomas in the proximal colon. METHODS: In a multicenter, prospective cohort trial, we matched 200 patients with normal FS and 200 patients with diminutive adenomas on FS for age and gender. All patients underwent colonoscopy. The presence of advanced adenomas (adenoma >or= 10 mm in diameter, villous adenoma, adenoma with high grade dysplasia, and colon cancer) and adenomas (any size) was recorded. Before colonoscopy, patients completed questionnaires about risk factors for adenomas. RESULTS: The prevalence of advanced adenomas in the proximal colon was similar in patients with diminutive adenomas and patients with normal FS (6% vs. 5.5%, respectively) (relative risk, 1.1; 95% confidence interval [CI], 0.5-2.6). Diminutive adenomas on FS did not accurately predict advanced adenomas in the proximal colon: sensitivity, 52% (95% CI, 32%-72%); specificity, 50% (95% CI, 49%-51%); positive predictive value, 6% (95% CI, 4%-8%); and negative predictive value, 95% (95% CI, 92%-97%). Male gender (odds ratio, 1.63; 95% CI, 1.01-2.61) was associated with an increased risk of proximal colon adenomas. CONCLUSIONS: Diminutive adenomas on sigmoidoscopy may not accurately predict advanced adenomas in the proximal colon.

Adenoma↗

PubMed1990

Outcome prediction models on admission in a medical intensive care unit: do they predict individual outcome?

Prospectively acquired data from 941 patients staying greater than 24 h in a medical ICU were analyzed to determine the relevance of scoring on ICU admission by the following methods of outcome prediction: Acute Physiology and Chronic Health Evaluation (APACHE II), Simplified Acute Physiology Score (SAPS), and Mortality Prediction Model (MPM). Analysis was performed separately for all patients (group A) and for a subsample (group B), obtained by excluding coronary care patients. Calculation of risk and classification of patients were carried out as recommended in the literature for MPM, APACHE II, and SAPS. In group A, sensitivities (correct prediction of hospital mortality) were 44.7%, 51.1%, and 21.2% and specificities (correct prediction of survival) were 84.5%, 85.4%, and 96.8%, respectively; overall correct classification rates were 73.3%, 75.8%, and 75.6%. In group B, sensitivities were slightly higher, but total correct classification rates did not reach group A levels. Goodness-of-fit testing showed low levels of fit for all methods in both groups. Application of APACHE II to diagnostic subgroups, using disease-adapted risk calculations, revealed marked inconsistencies between the estimated risk and the observed mortality. We conclude that the estimation of risk on admission by the three methods investigated might be helpful for global comparisons of ICU populations, although the lack of disease specificity reduces their applicability for severity grading of a given illness. The inaccuracy of these methods makes them ineffective for predicting individual outcome; thus, they provide little advantage in clinical decision-making.

Female↗

PubMed1998

Predicting in-hospital deaths from coronary artery bypass graft surgery. Do different severity measures give different predictions?

OBJECTIVES: Severity-adjusted death rates for coronary artery bypass graft (CABG) surgery by provider are published throughout the country. Whether five severity measures rated severity differently for identical patients was examined in this study. METHODS: Two severity measures rate patients using clinical data taken from the first two hospital days (MedisGroups, physiology scores); three use diagnoses and other information coded on standard, computerized hospital discharge abstracts (Disease Staging, Patient Management Categories, all patient refined diagnosis related groups). The database contained 7,764 coronary artery bypass graft patients from 38 hospitals with 3.2% in-hospital deaths. Logistic regression was performed to predict deaths from age, age squared, sex, and severity scores, and c statistics from these regressions were used to indicate model discrimination. Odds ratios of death predicted by different severity measures were compared. RESULTS: Code-based measures had better c statistics than clinical measures: all patient refined diagnosis related groups, c = 0.83 (95% C.I. 0.81, 0.86) versus MedisGroups, c = 0.73 (95% C.I. 0.70, 0.76). Code-based measures predicted very different odds of dying than clinical measures for more than 30% of patients. Diagnosis codes indicting postoperative, life-threatening conditions may contribute to the superior predictive power of code-based measures. CONCLUSIONS: Clinical and code-based severity measures predicted different odds of dying for many coronary artery bypass graft patients. Although code-based measures had better statistical performance, this may reflect their reliance on diagnosis codes for life-threatening conditions occurring late in the hospitalization, possibly as complications of care. This compromises their utility for drawing inferences about quality of care based on severity-adjusted coronary artery bypass graft death rates.

Coronary Artery Bypass↗

PubMed2004

Assessment of the enhancement in predictive accuracy provided by systematic biopsy in predicting outcome for clinically localized prostate cancer.

PURPOSE: Current localized prostate cancer treatment outcome nomograms rely on prostate specific antigen (PSA), tumor stage and grade. We investigated whether the addition of prostate biopsy features may enhance the accuracy of a nomogram predicting recurrence after radical prostatectomy (RP). MATERIALS AND METHODS: Clinical data from 1,152 patients who underwent RP were used and included PSA, clinical stage, biopsy Gleason grade and systematic biopsy information that quantified the amount of cancer and high grade cancer. Predictive accuracy for freedom from recurrence after RP was assessed with and without tumor quantification in the biopsy by the area under the receiver operating characteristics curve (AUC). RESULTS: Percentage and number of cores with cancer, and percentage and number of cores with high grade cancer were predictors of outcome when added to models that included PSA, Gleason grade and clinical stage (all p <0.0001). Nomogram accuracy with 3 traditional variables (AUC 0.790) was minimally enhanced with the addition of percentage or number of positive cores (AUC 0.804 and 0.800, respectively), or percentage or number of cores with high grade cancer (AUC 0.802 and 0.800, respectively). Maximum predictive accuracy of 0.811 was achieved after supplementing the traditional 3-variable nomogram with various combinations of additional pathological predictors. CONCLUSIONS: The information provided by systematic biopsies substantially improves the ability to predict outcome following RP. However, some incremental predictive accuracy was achieved by adding systematic biopsy features.

Adult↗