A Comparison of NASA Induction Tools for the Creation of Decision Rules Regarding Treatment for Clinically Localized Prostate Cancer

The final report includes project information, a project summary, and a short bibliography listing contributors to the project, articles written and book chapters written as a result of the project

Age and Prostate-Specific Antigen Level Prior to Diagnosis Predict Risk of Death from Prostate Cancer.

A single early prostate-specific antigen (PSA) level has been correlated with a higher likelihood of prostate cancer diagnosis and death in younger men. PSA testing in older men has been considered of limited utility. We evaluated prostate cancer death in relation to age and PSA level immediately prior to prostate cancer diagnosis. Using the Veterans Affairs database, we identified 230,081 men aged 50-89 years diagnosed with prostate cancer and at least one prior PSA test between 1999 and 2009. Prostate cancer-specific death over time was calculated for patients stratified by age group (e.g., 50-59 years, through 80-89 years) and PSA range at diagnosis (10 ranges) using Kaplan-Meier methods. Risk of 10-year prostate cancer mortality across age and PSA was compared using log-rank tests with a Bonferroni adjustment for multiple testing. 10.5% of men diagnosed with prostate cancer died of cancer during the 10-year study period (mean follow-up = 3.7 years). Higher PSA values prior to diagnosis predict a higher risk of death in all age groups (p < 0.0001). Within the same PSA range, older age groups are at increased risk for death from prostate cancer (p < 0.0001). For PSA of 7-10 ng/mL, cancer-specific death, 10 years after diagnosis, increased from 7% for age 50-59 years to 51% for age 80-89 years. Men older than 70 years are more likely to die of prostate cancer at any PSA level than younger men, suggesting prostate cancer remains a significant problem among older men (even those aged 80+) and deserves additional study

A first step towards a global nomogram to predict disease progression for men on active surveillance

Background: Signs of disease progression (28%) and conversion to active treatment without evidence of disease progression (13%) are the main reasons for discontinuation of active surveillance (AS) in men with localised prostate cancer (PCa). We aimed to develop a nomogram to predict disease progression in these patients. Methods: As a first step in the development of a nomogram, using data from Movembers' GAP3 Consortium (n=14,380), we assessed heterogeneity between centres in terms of risk of disease progression. We started with assessment of baseline hazards for disease progression based on grouping of centres according to follow-up protocols [high: yearly; intermediate: similar to 2 yearly; and low: at year 1, 4 & 7 (i.e., PRIAS)]. We conducted cause-specific random effect Cox proportional hazards regression to estimate risk of disease progression by centre in each group. Results: Disease progression rates varied substantially between centres [median hazard ratio (MHR): 2.5]. After adjustment for various clinical factors (age, year of diagnosis, Gleason grade group, number of positive cores and PSA), substantial heterogeneity in disease progression remained between centres. Conclusions: When combining worldwide data on AS, we noted unexplained differences of disease progression rate even after adjustment for various clinical factors. This suggests that when developing a global nomogram, local adjustments for differences in risk of disease progression and competing outcomes such as conversion to active treatment need to be considered.Peer reviewe

Assessing quality of life in men with clinically localized prostate cancer: Development of a new instrument for use in multiple settings

Background : Quality of life in prostate cancer patients with clinically localized disease has become the focus of increasing attention over the past decade. However, few instruments have been developed and validated to assess quality of life specifically in this patient population. Objective : The purpose of this investigation was to create a comprehensive, multi-scale quality of life instrument that can be tailored to the needs of the clinician/investigator in multiple settings. Design , subjects , and measures : Patients diagnosed with clinically localized prostate cancer were mailed a questionnaire consisting of new and previously validated quality of life items and ancillary scales. Data from returned questionnaires were analyzed and used to create a multi-scale instrument that assesses the effects of treatment and disease on urinary, sexual, and bowel domains, supplemented by a scale assessing anxiety over disease course/effectiveness of treatment. The instrument was then mailed to a second sample of prostate cancer patients once and then again two weeks later to assess test–retest reliability. To assess feasibility in clinical settings, the instrument was self-administered to a third patient sample during a urology clinic visit. Results : All scales exhibited good internal consistency and test–retest reliability, convergent and discriminant validity, and significant correlations with disease specific, generic health-related, and global measures of quality of life. Men with greater physiologic impairment reported more limitations in role activities and more bother. Scales were also able to differentiate patients undergoing different therapies. All scales exhibited negligible correlations with a measure of socially desirable responding. Additionally, the instrument proved feasible when used as a self-administered questionnaire in a clinical setting. Conclusions : The current instrument possesses brief multi-item scales that can be successfully self-administered in multiple settings. The instrument is flexible, relatively quick, psychometrically reliable and valid, and permits a more comprehensive assessment of patients' quality of life.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43571/1/11136_2004_Article_282460.pd

A simulation model of colorectal cancer surveillance and recurrence

BACKGROUND: Approximately one-third of those treated curatively for colorectal cancer (CRC) will experience recurrence. No evidence-based consensus exists on how best to follow patients after initial treatment to detect asymptomatic recurrence. Here, a new approach for simulating surveillance and recurrence among CRC survivors is outlined, and development and calibration of a simple model applying this approach is described. The model’s ability to predict outcomes for a group of patients under a specified surveillance strategy is validated. METHODS: We developed an individual-based simulation model consisting of two interacting submodels: a continuous-time disease-progression submodel overlain by a discrete-time Markov submodel of surveillance and re-treatment. In the former, some patients develops recurrent disease which probabilistically progresses from detectability to unresectability, and which may produce early symptoms leading to detection independent of surveillance testing. In the latter submodel, patients undergo user-specified surveillance testing regimens. Parameters describing disease progression were preliminarily estimated through calibration to match five-year disease-free survival, overall survival at years 1–5, and proportion of recurring patients undergoing curative salvage surgery from one arm of a published randomized trial. The calibrated model was validated by examining its ability to predict these same outcomes for patients in a different arm of the same trial undergoing less aggressive surveillance. RESULTS: Calibrated parameter values were consistent with generally observed recurrence patterns. Sensitivity analysis suggested probability of curative salvage surgery was most influenced by sensitivity of carcinoembryonic antigen assay and of clinical interview/examination (i.e. scheduled provider visits). In validation, the model accurately predicted overall survival (59% predicted, 58% observed) and five-year disease-free survival (55% predicted, 53% observed), but was less accurate in predicting curative salvage surgery (10% predicted; 6% observed). CONCLUSIONS: Initial validation suggests the feasibility of this approach to modeling alternative surveillance regimens among CRC survivors. Further calibration to individual-level patient data could yield a model useful for predicting outcomes of specific surveillance strategies for risk-based subgroups or for individuals. This approach could be applied toward developing novel, tailored strategies for further clinical study. It has the potential to produce insights which will promote more effective surveillance—leading to higher cure rates for recurrent CRC

Разработка и валидация номограммы, позволяющей прогнозировать выживаемость без прогрессирования при терапии пазопанибом по поводу распространенного рака почки

Цель исследования – разработка и валидация номограммы, позволяющей прогнозировать 12-месячную выживаемость без прогрессирования (ВБП) у пациентов, получающих пазопаниб в качестве первой линии терапии распространенного рака почки.Материалы и методы. Проведено статистическое моделирование данных 557 пациентов, получавших пазопаниб, в исследовании III фазы COMPARZ. Известные прогностические факторы были внесены в мультивариантную модель по Cox. Рассмотренные параметры включали уровень нейтрофилов, содержание альбумина и щелочной фосфатазы в сыворотке, время между постановкой диагноза и началом лечения, а также наличие костных метастазов. Для валидации были использованы данные по группе участников плацебоконтролируемого исследования III фазы, получавших пазопаниб.Результаты. Данная модель включала 10 прогностических факторов, представленных в виде номограммы, позволяющей прогнозировать 12-месячную ВБП. Сопоставления, проведенные с целью калибровки разработанной модели, позволяют предполагать достаточное соответствие расчетных вероятностей ВБП ее фактическим показателям. Индекс конкордантности для 12-месячной ВБП составил 0,625. Отмечена достоверная взаимосвязь (p < 0,05) между ВБП и наличием костных метастазов, интервалом времени между постановкой диагноза и началом лечения, а также уровнями альбумина и щелочной фосфатазы. Прогностическая роль последних 2 параметров оказалась весьма существенной.Выводы. Номограмма позволяет с достаточной точностью прогнозировать ВБП у пациентов с распространенным раком почки, получающих пазопаниб, в зависимости от исходных клинических характеристик.Цель исследования – разработка и валидация номограммы, позволяющей прогнозировать 12-месячную выживаемость без прогрессирования (ВБП) у пациентов, получающих пазопаниб в качестве первой линии терапии распространенного рака почки.Материалы и методы. Проведено статистическое моделирование данных 557 пациентов, получавших пазопаниб, в исследовании III фазы COMPARZ. Известные прогностические факторы были внесены в мультивариантную модель по Cox. Рассмотренные параметры включали уровень нейтрофилов, содержание альбумина и щелочной фосфатазы в сыворотке, время между постановкой диагноза и началом лечения, а также наличие костных метастазов. Для валидации были использованы данные по группе участников плацебоконтролируемого исследования III фазы, получавших пазопаниб.Результаты. Данная модель включала 10 прогностических факторов, представленных в виде номограммы, позволяющей прогнозировать 12-месячную ВБП. Сопоставления, проведенные с целью калибровки разработанной модели, позволяют предполагать достаточное соответствие расчетных вероятностей ВБП ее фактическим показателям. Индекс конкордантности для 12-месячной ВБП составил 0,625. Отмечена достоверная взаимосвязь (p < 0,05) между ВБП и наличием костных метастазов, интервалом времени между постановкой диагноза и началом лечения, а также уровнями альбумина и щелочной фосфатазы. Прогностическая роль последних 2 параметров оказалась весьма существенной.Выводы. Номограмма позволяет с достаточной точностью прогнозировать ВБП у пациентов с распространенным раком почки, получающих пазопаниб, в зависимости от исходных клинических характеристик

Guidelines for reporting of statistics for clinical research in urology

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148242/1/bju14640.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148242/2/bju14640_am.pd

Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

Objective: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors from the end-user. Study Design and Setting: Ten North American and European cohorts from the Prostate Biopsy Collaborative Group (PBCG) were used for fitting a risk prediction tool for clinically significant prostate cancer, defined as Gleason grade group greater or equal 2 on standard TRUS prostate biopsy. One large European PBCG cohort was withheld for external validation, where calibration-in-the-large (CIL), calibration curves, and area-underneath-the-receiver-operating characteristic curve (AUC) were evaluated. Ten-fold leave-one-cohort-internal validation further validated the optimal missing data approach. Results: Among 12,703 biopsies from 10 training cohorts, 3,597 (28%) had clinically significant prostate cancer, compared to 1,757 of 5,540 (32%) in the external validation cohort. In external validation, the available cases method that pooled individual patient data containing all risk factors input by an end-user had best CIL, under-predicting risks as percentages by 2.9% on average, and obtained an AUC of 75.7%. Imputation had the worst CIL (-13.3%). The available cases method was further validated as optimal in internal cross-validation and thus used for development of an online risk tool. For end-users of the risk tool, two risk factors were mandatory: serum prostate-specific antigen (PSA) and age, and ten were optional: digital rectal exam, prostate volume, prior negative biopsy, 5-alpha-reductase-inhibitor use, prior PSA screen, African ancestry, Hispanic ethnicity, first-degree prostate-, breast-, and second-degree prostate-cancer family history