Prostatic Neoplasms: Kattan MW

Arlen PM, Bianco F, Dahut WL, D'Amico A, Figg WD, Freedland SJ, Gulley JL, Kantoff PW, Kattan MW, Lee A, Regan MM, Sartor O, Anonymous00032. · Medical Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland 20892, USA. · J Urol. · Pubmed #18423743 links to  free full text

Abstract: PURPOSE: Prostate specific antigen is a glycoprotein found almost exclusively in normal and neoplastic prostate cells. Prostate specific antigen doubling time, or the change in prostate specific antigen over time, has emerged as a useful predictive marker for assessing disease outcome in patients with prostate cancer. It is important to agree on definitions and values for the calculation of prostate specific antigen doubling time, and to develop a common approach to outcome analysis and reporting. MATERIALS AND METHODS: In September 2006 a conference was held at the National Cancer Institute in Bethesda, Maryland to define these parameters and develop guidelines for their use. RESULTS: The Prostate Specific Antigen Working Group defined criteria regarding prostate specific antigen doubling time including the calculation of prostate specific antigen doubling time, evidence to support prostate specific antigen doubling time as a predictive factor in the setting of biochemical recurrence and the use of prostate specific antigen doubling time as a stratification factor in clinical trials. CONCLUSIONS: We propose that investigators calculate prostate specific antigen doubling time before enrolling patients in clinical studies and calculate it as an additional measurement of therapeutic activity. We believe we have developed practical guidelines for the calculation of prostate specific antigen doubling time and its use as a measurement of prognosis and outcome. Furthermore, the use of common standards for prostate specific antigen doubling time in clinical trials is important as we determine which treatments should progress to randomized trials in which "hard" end points such as survival will be used.

Scher HI, Eisenberger M, D'Amico AV, Halabi S, Small EJ, Morris M, Kattan MW, Roach M, Kantoff P, Pienta KJ, Carducci MA, Agus D, Slovin SF, Heller G, Kelly WK, Lange PH, Petrylak D, Berg W, Higano C, Wilding G, Moul JW, Partin AN, Logothetis C, Soule HR. · Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10021, USA. · J Clin Oncol. · Pubmed #14752077 No free full text.

Abstract: PURPOSE: To define methodology to show clinical benefit for patients in the state of a rising prostate-specific antigen (PSA). RESULTS: Hypothesis: A clinical states framework was used to address the hypothesis that definitive phase III trials could not be conducted in this patient population. Patient Population: The Group focused on men with systemic (nonlocalized) recurrence and a defined risk of developing clinically detectable metastases. Models to define systemic versus local recurrence, and risk of metastatic progression were discussed. Intervention: Therapies that have shown favorable effects in more advanced clinical states; meaningful biologic surrogates of activity linked with efficacy in other tumor types; and/or effects on a target or pathway known to contribute to prostate cancer progression in this state can be considered for evaluation. Outcomes: An intervention-specific posttherapy PSA-based outcome definition that would justify further testing should be described at the outset. Reporting: Trial reports should include a table showing the number of patients who achieve a specific PSA-based outcome, the number who remain enrolled onto the trial, and the number who came off study at different time points. The term PSA response should be abandoned. Trial Design: The phases of drug development for this state are optimizing dose and schedule, demonstration of a treatment effect, and clinical benefit. To move a drug forward should require a high bar that includes no rise in PSA in a defined proportion of patients for a specified period of time at a minimum. Agents that do not produce this effect can only be tested in combination. The preferred end point of clinical benefit is prostate cancer-specific survival; the time to development of metastatic disease is an alternative. CONCLUSION: Methodology to show that an intervention alters the natural history of prostate cancer is described. At each stage of development, only agents with sufficient activity should be moved forward.

Kattan MW. · No affiliation provided · J Urol. · Pubmed #18343424 No free full text.

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Kattan MW. · No affiliation provided · Eur Urol. · Pubmed #18207318 No free full text.

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Kattan MW. · No affiliation provided · Eur Urol. · Pubmed #18093723 No free full text.

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Hixson ED, Kattan MW. · No affiliation provided · Eur Urol. · Pubmed #16439054 No free full text.

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Kattan MW. · No affiliation provided · J Natl Cancer Inst. · Pubmed #12734304 links to  free full text

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Shariat SF, Karakiewicz PI, Roehrborn CG, Kattan MW. · Department of Urology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA. · Cancer. · Pubmed #18823041 No free full text.

Abstract: Accurate estimates of risk are essential for physicians if they are to recommend a specific management to patients with prostate cancer. Accurate risk estimates also are required for clinical trial design to ensure that homogeneous, high-risk patient groups are used to investigate new cancer therapeutics. Using the MEDLINE database, a literature search was performed on prostate cancer predictive tools from January 1966 to July 2007. The authors recorded input variables, the prediction form, the number of patients used to develop prediction tools, the outcome being predicted, prediction tool-specific features, predictive accuracy, and whether validation was performed. Each prediction tool was classified into patient clinical disease state and the outcome being predicted. First, the authors described the criteria for evaluation (predictive accuracy, calibration, generalizability, head-to-head comparison, and level of complexity) and the limitations of current predictive tools. The literature search generated 109 published prediction tools, including only 68 that had undergone validation. An increasing number of predictive tools addressed important endpoints, such as disease recurrence, metastasis, and survival. Despite their limitations and the limitations of data, predictive tools are essential for individualized, evidence-based medical decision making. Moreover, the authors recommend wider adoption of risk-prediction models in the design and implementation of clinical trials. Among prediction tools, nomograms provide superior, individualized, disease-related risk estimations that facilitate management-related decisions. Nevertheless, many more predictive tools, comparisons between them, and improvements to existing tools are needed.

Shariat SF, Karakiewicz PI, Suardi N, Kattan MW. · Department of Urology, University of Texas Southwestern Medical Centre, Dallas, Texas, USA. · Clin Cancer Res. · Pubmed #18628454 links to  free full text

Abstract: PURPOSE: Accurate estimates of risk are essential for physicians if they are to recommend a specific management to patients with prostate cancer. Accurate risk estimates are also required for clinical trial design, to ensure homogeneous patient groups. Because there is more than one model available for prediction of most outcomes, model comparisons are necessary for selection of the best model. We describe the criteria based on which to judge predictive tools, describe the limitations of current predictive tools, and compare the different predictive methodologies that have been used in the prostate cancer literature. EXPERIMENTAL DESIGN: Using MEDLINE, a literature search was done on prostate cancer decision aids from January 1966 to July 2007. RESULTS: The decision aids consist of nomograms, risk groupings, artificial neural networks, probability tables, and classification and regression tree analyses. The following considerations need to be applied when the qualities of predictive models are assessed: predictive accuracy (internal or ideally external validation), calibration (i.e., performance according to risk level or in specific patient subgroups), generalizability (reproducibility and transportability), and level of complexity relative to established models, to assess whether the new model offers advantages relative to available alternatives. Studies comparing decision aids have shown that nomograms outperform the other methodologies. CONCLUSIONS: Nomograms provide superior individualized disease-related risk estimations that facilitate management-related decisions. Of currently available prediction tools, the nomograms have the highest accuracy and the best discriminating characteristics for predicting outcomes in prostate cancer patients.

Schröder F, Kattan MW. · Department of Urology, Erasmus Medical Centre, Rotterdam, The Netherlands. · Eur Urol. · Pubmed #18511177 No free full text.

Abstract: CONTEXT: The sensitivity and specificity profile of measuring levels of prostate-specific antigen (PSA) to select men for prostate biopsy is not optimal. This has prompted the construction of nomograms and artificial neural networks (ANNs) to increase the performance of PSA measurements. OBJECTIVE: A systematic review of nomograms and ANNs designed to predict the risk of a positive prostate biopsy for cancer was conducted in order to determine their value versus measuring PSA levels alone. EVIDENCE ACQUISITION: Medical Literature Analysis and Retrieval System Online (U.S. National Library of Medicine's life science database; MEDLINE) was searched using the terms "nomogram" "artificial neural network" and "prostate cancer" for dates up to and including July 2007 and was supplemented by manual searches of reference lists. Included studies used an assessment tool to examine the risk of a positive prostate biopsy in a man without a known cancer diagnosis. Intramodel comparisons with evaluation of PSA levels alone, and intermodel comparisons of area under the curve (AUC) from receiver operating characteristic (ROC) curves were conducted. Individual case examples were also used for comparisons. EVIDENCE SYNTHESIS: Twenty-three studies examining 36 models were included. With the exception of two studies, all the models had AUC values of 0.70 or greater, with eight reporting an AUC of >/=0.80 and four (all ANNs) reporting an AUC >/=0.85, with variable validation status. Fourteen studies compared the AUC with PSA levels alone: all showed a benefit from using AUCs which varied from 0.02 to 0.26. Of the 16 external validation comparisons, in 13 the AUC was lower in the external population than in the model population. CONCLUSIONS: Nomograms and ANNs produce improvements in AUC over measurement of PSA levels alone, but many lack external validation. Where this is available, the benefits are often diminished, although most remain significantly better than with evaluation of PSA levels alone. In men without additional risk factors, PSA cutoff values alone provide a relatively precise risk estimate, but if additional risk factors are known, PSA values alone are less accurate.

Shariat SF, Karakiewicz PI, Margulis V, Kattan MW. · Department of Urology, University of Texas Southwestern Medical Centre, Dallas, Texas 75390-9110, USA. · Curr Opin Urol. · Pubmed #18382238 No free full text.

Abstract: PURPOSE OF REVIEW: We created an inventory of current predictive tools available for prostate cancer. This review may serve as an initial step toward a comprehensive reference guide for physicians to locate published nomograms that apply to the clinical decision in question. Using MEDLINE a literature search was performed on prostate cancer predictive tools from January 1966 to November 2007. We describe the patient populations to which they apply and the outcomes predicted, and record their individual characteristics. RECENT FINDINGS: The literature search generated 111 published prediction tools that may be applied to patients in various clinical stages of disease. Of the 111 prediction tools, only 69 had undergone validation. We present an inventory of models with input variables, prediction form, number of patients used to develop the prediction tools, the outcome being predicted, prediction tool-specific features, predictive accuracy, and whether validation was performed. SUMMARY: Decision rules, such as nomograms, provide evidence-based and at the same time individualized predictions of the outcome of interest. Such predictions have been repeatedly shown to be more accurate than those of clinicians, regardless of their level of expertise. Accurate risk estimates are also required for clinical trial design, to ensure homogeneous high-risk patient groups for whom new cancer therapeutics will be investigated.

Stephenson AJ, Kattan MW. · Section of Urologic Oncology, Glickman Urological Institute, Lerner College of Medicine, Cleveland, OH, USA. · BJU Int. · Pubmed #16831140 No free full text.

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Mottet N, Prayer-Galetti T, Hammerer P, Kattan MW, Tunn U. · Department of Urology, Clinique Mutualiste, St Etienne, France. · BJU Int. · Pubmed #16566812 No free full text.

Abstract: We review the effectiveness of androgen-deprivation therapy (ADT) in the management of prostate cancer, and the effect that this treatment has on a patient's quality of life (QoL), based on discussions held at a European symposium on the management of prostate cancer. The overall QoL is reduced in asymptomatic men, and there are known decreases in cognitive function, self-esteem, libido and sexual function. Hot flashes are also a frequent problem. Prolonged ADT can lead to osteoporosis and subsequently fractures. Various effective methods exist to manage and minimize these side-effects; some are specific to the side-effect, whereas other more general methods include lifestyle changes, specific drugs and added hormonal manipulations. Intermittent ADT for patients taking luteinizing hormone-releasing hormone agonists offers a promising method to reduce adverse effects, and possibly increases the time to androgen independence. Initial studies indicate that prostate-specific antigen-based progression with intermittent ADT is similar to that seen with continuous ADT, but there is a reduction in side-effects, leading to an improvement in QoL.

Hammerer PG, Kattan MW, Mottet N, Prayer-Galetti T. · Department of Urology, Academic Hospital, Braunschweig, Germany. · BJU Int. · Pubmed #16566811 No free full text.

Abstract: We review the role of prostate-specific antigen (PSA) and the importance of patient education in the management of prostate cancer, based on discussions held at a European symposium on managing prostate cancer. Although PSA is the most widely used serum marker for detecting prostate cancer and for monitoring treatment responses, its use as a diagnostic marker is controversial due to concerns of over-diagnosis and low specificity. PSA isoforms, as well as PSA doubling time, might improve the specificity for earlier prostate cancer detection and can be used as surrogate markers for treatment efficacy. Patients can differ considerably in the importance they place on health-related quality of life aspects and fear of cancer progression. Consequently, there needs to be active, educated discussion of risk and outcomes between physicians and patients. Risk assessment tools, e.g. validated nomograms, enable clinicians to improve their decision analysis and form the basis for subsequent discussion of treatment options between the physician and patient, thereby enabling informed consent and appropriate decision-making.

Kattan MW. · Department of Quantitative Health Sciences, Cleveland Clinic Foundation, OH, USA. · Urol Nurs. · Pubmed #16562382 No free full text.

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Boccon-Gibod L, Djavan WB, Hammerer P, Hoeltl W, Kattan MW, Prayer-Galetti T, Teillac P, Tunn UW. · CHU Bichat, Department of Urology, Paris, France. · Int J Clin Pract. · Pubmed #15161124 No free full text.

Abstract: A European Consensus on the management of prostate-specific antigen (PSA) relapse in patients with prostate cancer has been formulated. The key recommendations proposed are that total PSA is the best detection tool for prostate cancer, with free and complexed PSA having a role in the PSA range 1-4 ng/ml. PSA relapse after radical prostatectomy (RP) has been defined as a value of 0.2 ng/ml with one subsequent rise, while the ASTRO definition should be used after radiotherapy. A PSA level of less than 0.4 ng/ml after hormonal therapy can be considered an indicator of a positive response. Continuous assessment using nomograms or artificial neural networks will help to determine whether progression after local therapy is distant or local, which is the basis for treatment decisions. Secondary treatment after local failure of RP should be initiated when PSA levels reach 1.0-1.5 ng/ml and salvage radiotherapy can be considered with or without hormonal therapy. Local failure after radiotherapy can be treated with a choice of high-intensity-focused ultrasound, salvage RP (only in highly selected patients), cryotherapy or external beam radiation. Treatment of distant failure involves hormonal manipulation, the type and the timing of which is based on both physician and patient preferences.

Kattan MW, Scardino PT. · Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA. · Clin Prostate Cancer. · Pubmed #15046699 No free full text.

Abstract: It is difficult to determine the pathologic stage of a clinically localized prostate cancer by physical examination or imaging studies. Consequently, clinicians rely on predictive models that estimate the probability of lymph node metastases and other pathologic features from clinical factors such as the clinical T stage, the grade in the biopsy specimen, and the serum prostate-specific antigen level. These models do not, however, directly predict prognosis. In developing a tool for predicting the probability that prostate cancer might recur after treatment, we took a novel approach that focused on the risk for the individual patient. In particular, we chose to develop a tool that calculates a continuous probability of recurrence rather than placing the patient in a risk group. This represents a fundamental departure from the classical goal of staging; a departure we argue is long overdue. Clinically localized prostate cancer patients deserve the most accurate and tailored predictions available, which current staging systems do not provide. Such an individualized approach should add value in medical decision making whenever an accurate prediction of the outcome may guide treatment selection.

Kattan MW, Eastham J. · Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA. · Clin Prostate Cancer. · Pubmed #15040880 No free full text.

Abstract: Nomograms are devices that predict outcome probabilities for the individual patient. Herein we discuss their strengths and limitations, focusing on responses to several frequently asked questions about nomograms. We believe these tools are useful and necessary for patient counseling, follow-up scheduling, and clinical trial design and analysis.

Diblasio CJ, Kattan MW. · Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA. · Urology. · Pubmed #14747038 No free full text.

Abstract: The generally indolent nature of prostate cancer, as well as the impact that treatment can have on quality of life (QOL) and cancer control, makes the decision analysis difficult for patients facing the task of selecting a treatment for clinically localized disease. Instruments to aid patients and their physicians in this decision analysis are needed. Nomograms are instruments that predict outcomes using specific clinical parameters. Nomograms use algorithms that incorporate several variables to calculate the predicted probability that a patient will achieve a particular clinical end point. Nomograms tend to outperform both clinical experts and predictive models using methods of risk grouping. We briefly outline the uses and limitations of nomograms, principles of nomogram construction, and the available models for predicting the progression-free probability after local definitive therapy with radical prostatectomy, external-beam radiotherapy, or brachytherapy. There is a need for additional nomograms that predict outcomes after salvage therapy, as well other clinical end points, including QOL-adjusted survival.

Di Blasio CJ, Rhee AC, Cho D, Scardino PT, Kattan MW. · Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA. · Semin Oncol. · Pubmed #14571407 No free full text.

Abstract: Due to the generally indolent nature of prostate cancer, patients must decide among a wide range of treatments, which will significantly affect both quality of life and survival. Thus, there is a need for instruments to aid patients and their physicians in decision analysis. Nomograms are instruments that predict outcomes for the individual patient. Using algorithms that incorporate multiple variables, nomograms calculate the predicted probability that a patient will reach a clinical end point of interest. Nomograms tend to outperform both expert clinicians and predictive instruments based on risk grouping. We outline principles for nomogram construction, including considerations for choice of clinical end points and appropriate predictive variables, and methods for model validation. Currently, nomograms are available to predict progression-free probability after several primary treatments for localized prostate cancer. There is need for additional models that predict other clinical end points, especially survival adjusted for quality of life.

Cho D, Di Blasio CJ, Rhee AC, Kattan MW. · Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA. · Urol Oncol. · Pubmed #12954499 No free full text.

Abstract: Androgen deprivation therapy (ADT) is a standard mode of therapy for patients with metastatic prostate cancer. Controversy exists, however, as to the optimal timing of initiation of ADT, as well as whether this form of therapy imparts a survival benefit to patients with advanced disease. Side effects of ADT are not minimal and can seriously compromise a patient's quality of life. Additionally, ADT eventually results in hormone-refractory prostate cancer (HRPC). Despite new chemotherapeutic regimens and hormonal agents, overall survival in these patients remains universally low. Nonetheless, it is valuable to gauge a patient's prognosis to assist in decision making when considering treatment options. Contemporary series analyzing patients with HRPC have identified several factors prognostic of survival outcomes, such as lactate dehydrogenase (LDH), alkaline phosphatase (ALK), hemoglobin (Hgb), and serum prostate specific antigen (PSA) level. Nomograms have been developed that utilize these pretreatment clinical variables to predict clinical outcomes, including 1-year, 2-year, and median survival times in patients with HRPC. These instruments are capable of more accurately predicting survival outcomes than traditional tables of multivariate results or simple analysis of prognostic factors. We believe these nomograms will become indispensable tools for patient counseling and clinical trial design in patients with HRPC.

Yossepowitch O, Trabulsi EJ, Kattan MW, Scardino PT. · Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. · Cancer Invest. · Pubmed #12901292 No free full text.

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Swindle PW, Kattan MW, Scardino PT. · Department of Urology, Sidney Kimmel Center for Prostate and Urologic Cancer, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10021, USA. · Urol Clin North Am. · Pubmed #12735513 No free full text.

Abstract: BCR is the most clinically used endpoint for identification of treatment failure. Approximately 15% to 53% of patients undergoing primary curative therapy will develop BCR. BCR often precedes clinically detectable recurrence by years. It does not necessarily translate directly into PCa morbidity and mortality, nor does it always reflect the desired endpoint. Furthermore, it has not been validated as a surrogate endpoint, in that interventions that have been shown to alter the PSA level have not been shown to also alter survival. The utility of PSA level as a surrogate endpoint is brought into question by the knowledge that the overall survival rate of patients at 10 years is similar in patients with and without BCR, and that in a significant proportion of men, the only evidence of disease during their lifetime will be a detectable PSA level. The likelihood of developing BCR post-therapy can be predicted by using multiple clinical and pathologic variables. With the development of nomograms that incorporate several markers, the accuracy of prediction has improved. Until recently, the natural history of BCR post-RRP has not been well understood. Pound et al showed the heterogenous and prolonged natural history of BCR. In this large series of men with BCR following RRP, only 34% of men developed metastatic disease. The median time from development of BCR to identification of metastases was 8 years, and the median time from the development of metastatic disease to death was just under 5 years. These data highlight the extremely variable and potentially indolent nature of BCR. The risk of metastatic disease following BCR has been relatively well defined and relates to PSADT and time to PSA recurrence. It generally is accepted that a PSADT of less than 6 to 10 months and a time to PSA recurrence of less than 1 to 2 years relates to a higher risk of developing metastatic disease. Local recurrence, however, remains poorly understood with respect to its true incidence, clinical significance, and natural history. The significance of BCR post-RT remains unclear due to the lack of data on its natural history. Attempts have been made to identify patients at high risk for metastatic progression by looking at time to PSA recurrence and PSADT. A PSADT of less than 6 to 12 months and a time to PSA recurrence of less than 12 months reflects a higher risk of developing metastatic disease. Accurate risk stratification by means of an algorithm similar to that produced by Pound et al has not been performed on a large cohort, thus making risk assessment for an individual patient difficult. The major dilemma for clinicians in the management of BCR is the identification of the site of disease recurrence, which ultimately guides therapy decisions. Clinicopathologic features allow for risk stratification for recurrence, and multiple investigations have attempted to localize the site of recurrence. Time to biochemical progression, Gleason score, and PSADT are predictive of the probability and time to development of metastatic disease, and allow for stratification of patients into different risk groups (see Table 2). TRUS, CT, PET, and DRE all have limited utility in the identification of local recurrence. ProstaScint and MRI have demonstrated encouraging initial results: however, they require further investigation. Bone scintigraphy is of little value for the initial investigation of BCR. In patients with a PSA level of less than 10 ng/mL, the risk of having a positive bone scan is less than 1% and, until the PSA level rises above 40 ng/mL, the risk of having a positive bone scan is less than 5%. Therefore, bone scintigraphy should be reserved for patients with a PSA level greater than 10 to 20 ng/mL or patients with a rapidly rising PSA level. Using new MRI sequences, there is some evidence that MRI is better for the detection of bony metastatic disease; however, this technique requires further investigation. BCR causes anxiety for the patient and the treating doctor, because the best way to manage patients with PSA-only progression is unknown. Currently, there are no validated treatment recommendations for the management of BCR. The information in this review provides the framework for assignment of patients into clinical trials based on different risk categories. Patients at high risk for metastatic progression could be identified early and thus entered into appropriate clinical trials for systemic therapies. Similarly, patients with a low risk of progression could be placed into observation protocols, potentially sparing them from exhaustive and inappropriate investigations.

Ross PL, Gerigk C, Gonen M, Yossepowitch O, Cagiannos I, Sogani PC, Scardino PT, Kattan MW. · Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA. · Semin Urol Oncol. · Pubmed #12012293 No free full text.

Abstract: When applying nomograms to a clinical setting it is essential to know how their predictions compare with clinicians'. Comparisons exist outside of the prostate cancer literature. We reviewed these comparisons and conducted 2 experiments comparing predictions of clinicians with prostate cancer nomograms. By using Medline, we searched studies from January 1966 to July 1999 that compared human predictions with nomogram predictions. Next, we conducted 2 experiments: (1) 17 urologists were presented with 10 case vignettes and asked to predict the 5-year recurrence-free probabilities for each patient; (2) case presentations of 63 prostate cancer patients (including full clinical histories with complete diagnostic data and surgical findings) were made to a group of 25 clinicians who were asked to predict organ-confined disease. We found 22 published studies comparing human experts with nomograms, greater than half (13 of 22) showed the nomogram performing above the level of the human expert. Our first experiment showed urologist modification of 165 nomogram predictions led to a decrease in prediction accuracy (c-index decreased from.67 to.55, P <.05). In our second experiment, clinician predictions of organ-confined disease were comparable to the nomogram (area under the receiver operating characteristic curve [AUC] 0.78 and 0.79, respectively). A mixed-model suggests the nomogram did not augment clinician prediction accuracy (doctor excess error 1.4%, P =.75, 95% confidence interval [CI]: -10.9% to 8.2%). Our data suggest that nomograms do not seem to diminish predictive accuracy and they may be of significant benefit in certain clinical decision making settings.

Kibel AS, Rosenbaum E, Kattan MW, Picus J, Dreicer R, Klein EA, Chatta GS, Nelson JB, DiPaola RS, Roth BJ, Cookson MS, Wilding G, Jarrard DF, Beer TM, Ryan CW, Petrylak DP, Benson MC, Partin AW, Garrett-Mayer E, Eisenberger MA. · Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri 63105, USA. · J Urol. · Pubmed #17437819 No free full text.

Abstract: PURPOSE: Patients with adverse pathological features are at high risk for recurrence following radical prostatectomy. To improve outcomes in this population we performed a phase II study of adjuvant docetaxel in these high risk patients. MATERIALS AND METHODS: Patients with nonmetastatic radical prostatectomy at greater than 50% risk for recurrence by 3 years were eligible. Pathological findings were centrally reviewed and risk assessment was based on a validated multivariate Cox proportional hazards model. Treatment consisted of 6 cycles of 35 mg/m(2) docetaxel weekly given 4 to 12 weeks following surgery. Progression was defined as a prostate specific antigen of 0.4 ng/ml or greater, radiological/pathological evidence of recurrent disease or death from any cause. To screen for the potential benefit of adjuvant weekly docetaxel we used nomogram predicted progression-free survival as a historical control. RESULTS: A total of 77 patients were registered between April 2002 and January 2004. Two patients had grade IV hyperglycemia and 20 had grade III toxicity. At a median followup of 29.2 months (range 1.6 to 39.2) 46 of 76 evaluable cases (60.5%) progressed. Observed median progression-free survival was 15.7 months (95% CI 12.8-25.1). Predicted median progression-free survival in a matched population was 10 months. Seven patients died, including 4 of prostate cancer, 1 with intra-abdominal bleeding during treatment and 2 of pneumonia and sudden cardiac death, respectively, following treatment. CONCLUSIONS: Adjuvant docetaxel for prostate cancer is feasible with significant reversible but acceptable toxicity. The actual median progression-free survival of 15.7 months was longer than the nomogram predicted rate for this patient population. Adjuvant docetaxel treatment should be further evaluated in phase III trials in patients with high risk prostate cancer.