Efficiency of the Breslow estimator in semiparametric transformation models.

Semiparametric transformation models for failure time data consist of a parametric regression component and an unspecified cumulative baseline hazard. The nonparametric maximum likelihood estimator (NPMLE) of the cumulative baseline hazard can be summarized in terms of weights introduced into a Breslow-type estimator (Weighted Breslow). At any given time point, the weights invoke an integral over the future of the cumulative baseline hazard, which presents theoretical and computational challenges. A simpler non-MLE Breslow-type estimator (Breslow) was derived earlier from a martingale estimating equation (MEE) setting observed and expected counts of failures equal, conditional on the past history. Despite much successful theoretical and computational development, the simpler Breslow estimator continues to be commonly used as a compromise between simplicity and perceived loss of full efficiency. In this paper we derive the relative efficiency of the Breslow estimator and consider the properties of the two estimators using simulations and real data on prostate cancer survival.

Outcomes after definitive radiation therapy for localized prostate cancer in a national health care delivery system.

PURPOSE: Accurate information regarding real-world outcomes after contemporary radiation therapy for localized prostate cancer is important for shared decision-making. Clinically relevant end points at 10 years among men treated within a national health care delivery system were examined. METHODS: National administrative, cancer registry, and electronic health record data were used for patients undergoing definitive radiation therapy with or without concurrent androgen deprivation therapy within the Veterans Health Administration from 2005 to 2015. National Death Index data were used through 2019 for overall and prostate cancer-specific survival and identified date of incident metastatic prostate cancer using a validated natural language processing algorithm. Metastasis-free, prostate cancer-specific, and overall survival using Kaplan-Meier methods were estimated. RESULTS: Among 41,735 men treated with definitive radiation therapy, the median age at diagnosis was 65 years and median follow-up was 8.7 years. Most had intermediate (42%) and high-risk (33%) disease, with 40% receiving androgen deprivation therapy as part of initial therapy. Unadjusted 10-year metastasis-free survival was 96%, 92%, and 80% for low-, intermediate-, and high-risk disease. Similarly, unadjusted 10-year prostate cancer-specific survival was 98%, 97%, and 90% for low-, intermediate-, and high-risk disease. The unadjusted overall survival was lower across increasing disease risk categories at 77%, 71%, and 62% for low-, intermediate-, and high-risk disease (p < .001). CONCLUSIONS: These data provide population-based 10-year benchmarks for clinically relevant end points, including metastasis-free survival, among patients with localized prostate cancer undergoing radiation therapy using contemporary techniques. The survival rates for high-risk disease in particular suggest that outcomes have recently improved.

An Interventional Response Phenotyping Study in Chronic Low Back Pain: Protocol for a Mechanistic Randomized Controlled Trial.

Evidence-based treatments for chronic low back pain (cLBP) typically work well in only a fraction of patients, and at present there is little guidance regarding what treatment should be used in which patients. Our central hypothesis is that an interventional response phenotyping study can identify individuals with different underlying mechanisms for their pain who thus respond differentially to evidence-based treatments for cLBP. Thus, we will conduct a randomized controlled Sequential, Multiple Assessment, Randomized Trial (SMART) design study in cLBP with the following three aims. Aim 1: Perform an interventional response phenotyping study in a cohort of cLBP patients (n = 400), who will receive a sequence of interventions known to be effective in cLBP. For 4 weeks, all cLBP participants will receive a web-based pain self-management program as part of a run-in period, then individuals who report no or minimal improvement will be randomized to: a) mindfulness-based stress reduction, b) physical therapy and exercise, c) acupressure self-management, and d) duloxetine. After 8 weeks, individuals who remain symptomatic will be re-randomized to a different treatment for an additional 8 weeks. Using those data, we will identify the subsets of participants that respond to each treatment. In Aim 2, we will show that currently available, clinically derived measures, can predict differential responsiveness to the treatments. In Aim 3, a subset of participants will receive deeper phenotyping (n = 160), to identify new experimental measures that predict differential responsiveness to the treatments, as well as to infer mechanisms of action. Deep phenotyping will include functional neuroimaging, quantitative sensory testing, measures of inflammation, and measures of autonomic tone.

A Gaussian copula approach for dynamic prediction of survival with a longitudinal biomarker.

Dynamic prediction uses patient information collected during follow-up to produce individualized survival predictions at given time points beyond treatment or diagnosis. This allows clinicians to obtain updated predictions of a patient's prognosis that can be used in making personalized treatment decisions. Two commonly used approaches for dynamic prediction are landmarking and joint modeling. Landmarking does not constitute a comprehensive probability model, and joint modeling often requires strong distributional assumptions and computationally intensive methods for estimation. We introduce an alternative approximate approach for dynamic prediction that aims to overcome the limitations of both methods while achieving good predictive performance. We separately specify the marker and failure time distributions conditional on surviving up to a prediction time of interest and use standard variable selection and goodness-of-fit techniques to identify the best-fitting models. Taking advantage of its analytic tractability and easy two-stage estimation, we use a Gaussian copula to link the marginal distributions smoothly at each prediction time with an association function. With simulation studies, we examine the proposed method's performance. We illustrate its use for dynamic prediction in an application to predicting death for heart valve transplant patients using longitudinal left ventricular mass index information.

A copula-based approach for dynamic prediction of survival with a binary time-dependent covariate.

Dynamic prediction methods incorporate longitudinal biomarker information to produce updated, more accurate predictions of conditional survival probability. There are two approaches for obtaining dynamic predictions: (1) a joint model of the longitudinal marker and survival process, and (2) an approximate approach that specifies a model for a specific component of the joint distribution. In the case of a binary marker, an illness-death model is an example of a joint modeling approach that is unified and produces consistent predictions. However, previous literature has shown that approximate approaches, such as landmarking, with additional flexibility can have good predictive performance. One such approach proposes using a Gaussian copula to model the joint distribution of conditional continuous marker and survival distributions. It has the advantage of specifying established, flexible models for the marginals for which goodness-of-fit can be assessed, and has easy estimation that can be implemented in standard software. In this article, we provide a Gaussian copula approach for dynamic prediction to accommodate a binary marker using a continuous latent variable formulation. We compare the predictive performance of this approach to joint modeling and landmarking using simulations and demonstrate its use for obtaining dynamic predictions in an application to a prostate cancer study.

The Effects of Intraoperative Caffeine on Postoperative Opioid Consumption and Related Outcomes After Laparoscopic Surgery: A Randomized Controlled Trial.

BACKGROUND: Surgical patients are vulnerable to opioid dependency and related risks. Clinical-translational data suggest that caffeine may enhance postoperative analgesia. This trial tested the hypothesis that intraoperative caffeine would reduce postoperative opioid consumption. The secondary objective was to assess whether caffeine improves neuropsychological recovery postoperatively. METHODS: This was a single-center, randomized, placebo-controlled trial. Participants, clinicians, research teams, and data analysts were all blinded to the intervention. Adult (≥18 years old) surgical patients (n = 65) presenting for laparoscopic colorectal and gastrointestinal surgery were randomized to an intravenous caffeine citrate infusion (200 mg) or dextrose 5% in water (40 mL) during surgical closure. The primary outcome was cumulative opioid consumption through postoperative day 3. Secondary outcomes included subjective pain reporting, observer-reported pain, delirium, Trail Making Test performance, depression and anxiety screens, and affect scores. Adverse events were reported, and hemodynamic profiles were also compared between the groups. RESULTS: Sixty patients were included in the final analysis, with 30 randomized to each group. The median (interquartile range) cumulative opioid consumption (oral morphine equivalents, milligrams) was 77 mg (33-182 mg) for caffeine and 51 mg (15-117 mg) for placebo (estimated difference, 55 mg; 95% confidence interval [CI], -9 to 118; P = .092). After post hoc adjustment for baseline imbalances, caffeine was associated with increased opioid consumption (87 mg; 95% CI, 26-148; P = .005). There were otherwise no differences in prespecified pain or neuropsychological outcomes between the groups. No major adverse events were reported in relation to caffeine, and no major hemodynamic perturbations were observed with caffeine administration. CONCLUSIONS: Caffeine appears unlikely to reduce early postoperative opioid consumption. Caffeine otherwise appears well tolerated during anesthetic emergence.

Top down or bottom up? An observational investigation of improvement in fibromyalgia symptoms following hip and knee replacement.

OBJECTIVES: Many patients with osteoarthritis have comorbid symptoms of FM, but it is unknown how these symptoms respond to surgical procedures that address nociceptive input in the periphery, such as total joint replacement. Here we explore differences in clinical characteristics between patients whose FM symptoms do and do not improve following total hip or knee replacement. METHODS: Participants were 150 patients undergoing knee or hip replacement who had a minimum FM survey score of 4 or greater prior to surgery. The top tertile of patients experiencing the most improvement in FM symptoms at month 6 were categorized as 'Improve' (n = 48) while the bottom two tertiles were categorized as 'Worsen/Same' (n = 102). Baseline symptom characteristics were compared between groups, as well as improvement in overall pain severity, surgical pain severity and physical function at 6 months. RESULTS: The Worsen/Same group had higher levels of fatigue, depression and surgical site pain at baseline (all P < 0.05). Additionally, they improved less on overall pain severity and physical functioning 6 months after surgery (both P < 0.05). CONCLUSION: Most patients derive significant benefit in improvement of comorbid FM symptoms following total joint replacement, but a substantial proportion do not. Understanding the neurobiological basis for these different trajectories may help inform clinical judgment and improve patient care.

Implementation of Evidence-Based Practice for Benign Paroxysmal Positional Vertigo in the Emergency Department: A Stepped-Wedge Randomized Trial.

STUDY OBJECTIVE: We evaluated a strategy to increase use of the test (Dix-Hallpike's test [DHT]) and treatment (canalith repositioning maneuver [CRM]) for benign paroxysmal positional vertigo in emergency department (ED) dizziness visits. METHODS: We conducted a stepped-wedge randomized trial in 6 EDs. The population was visits with dizziness as a principal reason for the visit. The intervention included educational sessions and decision aid materials. Outcomes were DHT or CRM documentation (primary), head computed tomography (CT) use, length of stay, admission, and 90-day stroke events. The analysis was multilevel logistic regression with intervention, month, and hospital as fixed effects and provider as a random effect. We assessed fidelity with monitoring intervention use and semistructured interviews. RESULTS: We identified 7,635 dizziness visits during 18 months. The DHT or CRM was documented in 1.5% of control visits (45/3,077; 95% confidence interval 1% to 1.9%) and 3.5% of intervention visits (159/4,558; 95% confidence interval 3% to 4%; difference 2%, 95% confidence interval 1.3% to 2.7%). Head CT use was lower in intervention visits compared with control visits (44.0% [1,352/3,077] versus 36.9% [1,682/4,558]). No differences were observed in admission or 90-day subsequent stroke risk. In fidelity evaluations, providers who used the materials typically reported positive clinical experiences but provider engagement was low at facilities without an emergency medicine residency program. CONCLUSION: These findings provide evidence that an implementation strategy of a benign paroxysmal positional vertigo-focused approach to ED dizziness visits can be successful and safe in promoting evidence-based care. Absolute rates of DHT and CRM use, however, were still low, which relates in part to our broad inclusion criteria for dizziness visits.

Has Smoking Cessation Increased? An Examination of the US Adult Smoking Cessation Rate 1990-2014.

INTRODUCTION: We examine the trajectory of adult smoking prevalence in the United States over the period 1990-2014 to investigate whether the smoking cessation rate has changed during this period. METHODS: We employ a dynamic model of smoking prevalence, and data from the National Health Interview Survey (NHIS) and the National Survey on Drug Use and Health (NSDUH), to estimate the adult cessation rate in 6-year intervals. We use weighted nonlinear least squares to perform the estimation. We then employ a meta-regression model to test whether the cessation rate has increased. RESULTS: The annual cessation rate has increased from 2.4% in 1990 to 4.5% in 2014 according to the NHIS data, and from 3.2% in 2002 to 4.2% in 2014 according to the NSDUH data. The increasing trend is statistically significant (p value = 1.57×10-6) and the two independent surveys produced nearly identical results, which makes it unlikely that our findings are a product of chance. CONCLUSIONS: Our analysis finds that the smoking cessation rate in the United States has almost doubled since 1990. This increase is responsible for at least 2 million fewer smokers in 2014. If current conditions persist, by the year 2020 the increase in cessation rates will be responsible for 3.5 million fewer smokers. Our findings can assist in predicting the future path of the smoking epidemic and determining the correct allocation of resources to eradicate it. IMPLICATIONS: We show that the adult smoking cessation rate has greatly increased since 1990. We demonstrate this by studying prevalence trajectories from two independent population surveys, which yielded nearly identical results. Different from other studies, we focus on permanent quit rates (net of relapses) which we estimate from a dynamic model of prevalence. Our results do not stem from self-reported quitting behavior, but from the analysis of observed prevalence and its inherent variability. Our findings can contribute to predicting the future path of the smoking epidemic and to determining the optimal allocation of resources to eradicate it.

Comparison of joint modeling and landmarking for dynamic prediction under an illness-death model.

Dynamic prediction incorporates time-dependent marker information accrued during follow-up to improve personalized survival prediction probabilities. At any follow-up, or "landmark", time, the residual time distribution for an individual, conditional on their updated marker values, can be used to produce a dynamic prediction. To satisfy a consistency condition that links dynamic predictions at different time points, the residual time distribution must follow from a prediction function that models the joint distribution of the marker process and time to failure, such as a joint model. To circumvent the assumptions and computational burden associated with a joint model, approximate methods for dynamic prediction have been proposed. One such method is landmarking, which fits a Cox model at a sequence of landmark times, and thus is not a comprehensive probability model of the marker process and the event time. Considering an illness-death model, we derive the residual time distribution and demonstrate that the structure of the Cox model baseline hazard and covariate effects under the landmarking approach do not have simple form. We suggest some extensions of the landmark Cox model that should provide a better approximation. We compare the performance of the landmark models with joint models using simulation studies and cognitive aging data from the PAQUID study. We examine the predicted probabilities produced under both methods using data from a prostate cancer study, where metastatic clinical failure is a time-dependent covariate for predicting death following radiation therapy.

Molecular profiling of ETS and non-ETS aberrations in prostate cancer patients from northern India.

BACKGROUND: Molecular stratification of prostate cancer (PCa) based on genetic aberrations including ETS or RAF gene-rearrangements, PTEN deletion, and SPINK1 over-expression show clear prognostic and diagnostic utility. Gene rearrangements involving ETS transcription factors are frequent pathogenetic somatic events observed in PCa. Incidence of ETS rearrangements in Caucasian PCa patients has been reported, however, occurrence in Indian population is largely unknown. The aim of this study was to determine the prevalence of the ETS and RAF kinase gene rearrangements, SPINK1 over-expression, and PTEN deletion in this cohort. METHODS: In this multi-center study, formalin-fixed paraffin embedded (FFPE) PCa specimens (n = 121) were procured from four major medical institutions in India. The tissues were sectioned and molecular profiling was done using immunohistochemistry (IHC), RNA in situ hybridization (RNA-ISH) and/or fluorescence in situ hybridization (FISH). RESULTS: ERG over-expression was detected in 48.9% (46/94) PCa specimens by IHC, which was confirmed in a subset of cases by FISH. Among other ETS family members, while ETV1 transcript was detected in one case by RNA-ISH, no alteration in ETV4 was observed. SPINK1 over-expression was observed in 12.5% (12/96) and PTEN deletion in 21.52% (17/79) of the total PCa cases. Interestingly, PTEN deletion was found in 30% of the ERG-positive cases (P = 0.017) but in only one case with SPINK1 over-expression (P = 0.67). BRAF and RAF1 gene rearrangements were detected in ∼1% and ∼4.5% of the PCa cases, respectively. CONCLUSIONS: This is the first report on comprehensive molecular profiling of the major spectrum of the causal aberrations in Indian men with PCa. Our findings suggest that ETS gene rearrangement and SPINK1 over-expression patterns in North Indian population largely resembled those observed in Caucasian population but differed from Japanese and Chinese PCa patients. The molecular profiling data presented in this study could help in clinical decision-making for the pursuit of surgery, diagnosis, and in selection of therapeutic intervention.

Semiparametric estimation in the proportional hazard model accounting for a misclassified cause of failure.

Misclassified causes of failures are a common phenomenon in competing risks survival data such as cancer mortality. We propose new estimating equations for a semiparametric proportional hazards (PH) model with misattributed causes of failures. Unlike other methods, the estimator does not require any parametric assumptions on baseline cause-specific hazard rates. It is shown that the estimators for regression coefficients are consistent and asymptotically normal. Simulation results support the theoretical analysis in finite samples. The methods are applied to analyze prostate cancer survival.

National Long-term Survival Estimates After Radical Prostatectomy for Prostate Cancer.

OBJECTIVE: To examine survival and disease control outcomes, including metastasis-related survival outcomes, in a large contemporary cohort of patients undergoing radical prostatectomy for localized prostate cancer. METHODS: We conducted a retrospective study of men with localized prostate cancer treated with radical prostatectomy from 2005 to 2015 with follow-up through 2019 in the Veterans Health Administration. We defined biochemical recurrence (BCR) as a prostate-specific antigen ≥0.2 ng/mL. We used a validated natural language processing encoded dataset to identify incident metastatic prostate cancer. We estimated overall survival from time of surgery, time of BCR, and time of first metastasis using the Kaplan-Meier method. We then estimated time from surgery to BCR, BCR to metastatic disease, and prostate-cancer-specific survival from various time points using cumulative incidence considering competing risk of death. RESULTS: Of 21,992 men undergoing radical prostatectomy, we identified 5951 (27%) who developed BCR. Of men with BCR, 677 (11%) developed metastases. We estimated the 10-year cumulative incidence of BCR and metastases after BCR were 28% and 20%, respectively. Median overall survival after BCR was 14years, with 10-year survival of 70%. From the time of metastasis, median overall survival approached 7years, with 10-year overall survival of 34%. Prostate cancer-specific survival for the entire cohort at 10years was 94%. CONCLUSION: In this large contemporary national cohort, survival for men with biochemically recurrent prostate cancer is longer than historical cohorts. When counseling patients and designing clinical studies, these updated estimates may serve as more reliable reflections of current outcomes.

Survival by first-line therapy and prognostic group among men with metastatic castration-resistant prostate cancer.

INTRODUCTION: Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease with prognoses varying from months to years at time of castration-resistant diagnosis. Optimal first-line therapy for those with different prognoses is unknown. METHODS: We conducted a retrospective cohort study of men in a national healthcare delivery system receiving first-line therapy for mCRPC (abiraterone, enzalutamide, docetaxel, or ketoconazole) from 2010 to 2017, with follow-up through 2019. Using commonly drawn prognostic labs at start of mCRPC therapy (hemoglobin, albumin, and alkaline phosphatase), we categorized men into favorable, intermediate, or poor prognostic groups depending on whether they had none, one to two, or all three laboratory values worse than designated laboratory cutoffs. We used Kaplan-Meier methods to examine prostate specific antigen (PSA) progression-free and overall survival (OS) according to prognostic group and first-line therapy, and multivariable cox regression to determine variables associated with survival outcomes. RESULTS: Among 4135 patients, median PSA progression-free survival (PFS) was 6.9 months (95% confidence interval [CI] 6.6-7.3), and median OS 18.8 months (95% CI 18.0-19.6), ranging from 5.7 months (95% CI 4.8-7.0) in the poor prognosis group to 31.3 months (95% CI 29.7-32.9) in the favorable group. OS was similar regardless of initial treatment received for favorable and intermediate groups, but worse for those in the poor prognostic group who received ketoconazole (adjusted hazard ratio 2.07, 95% CI 1.2-3.6). PSA PFS was worse for those who received ketoconazole compared to abiraterone across all prognostic groups (favorable HR 1.76, 95% CI 1.34-2.31; intermediate HR 1.78, 95% CI 1.41-2.25; poor HR 8.01, 95% CI 2.93-21.9). CONCLUSION: Commonly drawn labs at mCRPC treatment start may aid in predicting survival and response to therapies, potentially informing discussions with care teams. First-line treatment selection impacts disease progression for all men with mCRPC regardless of prognostic group, but impacted OS only for men with poor prognosis at treatment start.

Isotonic estimation of survival under a misattribution of cause of death.

Several authors have indicated that incorrectly classified cause of death for prostate cancer survivors may have played a role in the observed recent peak and decline of prostate cancer mortality. Motivated by the suggestion we studied a competing risks model where other cause of death may be misattributed as a death of interest. We first consider a naïve approach using unconstrained nonparametric maximum likelihood estimation (NPMLE), and then present the constrained NPMLE where the survival function is forced to be monotonic. Surprising observations were made as we studied their small-sample and asymptotic properties in continuous and discrete situations. Contrary to the common belief that the non-monotonicity of a survival function NPMLE is a small-sample problem, the constrained NPMLE is asymptotically biased in the continuous setting. Other isotonic approaches, the supremum (SUP) method and the Pooled-Adjacent-Violators (PAV) algorithm, and the EM algorithm are also considered. We found that the EM algorithm is equivalent to the constrained NPMLE. Both SUP method and PAV algorithm deliver consistent and asymptotically unbiased estimator. All methods behave well asymptotically in the discrete time setting. Data from the Surveillance, Epidemiology and End Results (SEER) database are used to illustrate the proposed estimators.

Better Understanding the Timing Of Androgen Deprivation Trial Outcomes: Impacts of Prior Androgen Deprivation Therapy.

BACKGROUND: The Timing Of Androgen Deprivation (TOAD) trial found an overall survival benefit for immediate vs delayed androgen deprivation therapy (ADT) for prostate-specific antigen (PSA)-relapsed or noncurable prostate cancer. However, broad eligibility criteria allowed entry of a heterogeneous participant group, including those with prior ADT exposure, raising concerns about subsequent androgen sensitivity. For these reasons, we completed previously specified subgroup analyses to assess if prior ADT was associated with ADT timing efficacy after PSA relapse. METHODS: We examined TOAD trial patient-level data for participants with PSA relapse after local therapy. We performed Kaplan-Meier analyses for overall survival stratified by prior ADT and randomized treatment arm (immediate or delayed ADT). We compared group characteristics using Mann-Whitney U and Fisher exact tests. All hypothesis tests were 2-sided. RESULTS: We identified 261 patients with PSA relapse, 125 of whom received prior ADT. Patients with prior ADT had higher PSA at presentation (12.1 vs 9.0 ng/mL; P < .001), more cT3 disease (38.4% vs 25.0%; P = .007), and more likely received radiotherapy as local treatment (80.0% vs 47.8%; P < .001) but were otherwise similar to patients without prior ADT exposure. Within this prior ADT group, those who received immediate ADT (n = 56) had improved overall survival compared with those who received delayed ADT (n = 69; P = .02). This benefit was not observed in the group with no prior ADT (P = .98). CONCLUSIONS: The survival benefit demonstrated in the TOAD trial may be driven by patients who received ADT prior to trial entry. We provide possible explanations for this finding with implications for treatment of PSA-relapsed prostate cancer and future study planning.

The genetic heterogeneity and drug resistance mechanisms of relapsed refractory multiple myeloma.

Multiple myeloma is the second most common hematological malignancy. Despite significant advances in treatment, relapse is common and carries a poor prognosis. Thus, it is critical to elucidate the genetic factors contributing to disease progression and drug resistance. Here, we carry out integrative clinical sequencing of 511 relapsed, refractory multiple myeloma (RRMM) patients to define the disease's molecular alterations landscape. The NF-κB and RAS/MAPK pathways are more commonly altered than previously reported, with a prevalence of 45-65% each. In the RAS/MAPK pathway, there is a long tail of variants associated with the RASopathies. By comparing our RRMM cases with untreated patients, we identify a diverse set of alterations conferring resistance to three main classes of targeted therapy in 22% of our cohort. Activating mutations in IL6ST are also enriched in RRMM. Taken together, our study serves as a resource for future investigations of RRMM biology and potentially informs clinical management.

Association of computerized mammographic parenchymal pattern measure with breast cancer risk: a pilot case-control study.

PURPOSE: To develop a computerized mammographic parenchymal pattern (MPP) measure and investigate its association with breast cancer risk. MATERIALS AND METHODS: A pilot case-control study was conducted by collecting mammograms from 382 subjects retrospectively. The study was institutional review board approved and HIPAA compliant. Informed consent was waived. The cases included the contralateral mammograms of cancer patients (n = 136) obtained at least 1 year before diagnosis. The controls included mammograms of healthy subjects (n = 246) who had cancer-free follow-up for at least 5 years. The data set was historically divided into a training set and an independent test set. An MPP measure was designed to analyze the texture patterns of fibroglandular tissue in the retroareolar region. Odds ratios (ORs) were used to assess the association between breast cancer risk and MPP. To test the trend in ORs, we divided the MPP measure into three categories (C1, C2, and C3) on the basis of its values from low to high, with C1 as the baseline. The confounding factors in this study included patient age, body mass index, first-degree relatives with history of breast cancer, number of previous breast biopsies, and percentage density (PD). RESULTS: Among all of the subjects from the training and test data sets, the Pearson product-moment correlation coefficient between MPP and PD was 0.13. With logistic regression to adjust the confounding, the adjusted ORs for C2 and C3 relative to C1 in the test set were 2.82 (P = .041) and 13.89 (P < .001), respectively. CONCLUSION: The proposed MPP measure demonstrated a strong association with breast cancer risk and has the potential to serve as an independent factor for risk prediction.

Effects of a high dose, aglycone-rich soy extract on prostate-specific antigen and serum isoflavone concentrations in men with localized prostate cancer.

The efficacy and safety of consuming high-dose isoflavone supplements for prostate cancer is not clear. A double-blind, placebo controlled, randomized trial was conducted in 53 men with prostate cancer enrolled in an active surveillance program. The treatment group consumed a supplement containing 450 mg genistein, 300 mg daidzein, and other isoflavones daily for 6 mo. Prostate-specific antigen (PSA) was measured in both groups at baseline, 3 mo, and 6 mo, and serum concentrations of genistein, daidzein, and equol were assessed at baseline and 6 mo in the treatment group. Following the completion of the 6-mo double-blind study, men were enrolled in a 6-mo open label trial with the same isoflavone-rich supplement, and PSA was measured at 3 and 6 mo. PSA concentrations did not change in either group after 6 mo or after 12 mo when the open-label study was included. The 6 mo serum concentrations of genistein and daidzein (39.85 and 45.59 µmol/l, respectively) were significantly greater than baseline values and substantially higher than levels previously reported in other studies. Equol levels did not change. Although high amounts of aglycone isoflavones may result in significantly elevated serum concentrations of genistein and daidzein, these dietary supplements alone did not lower PSA levels in men with low-volume prostate cancer.