A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk.

A reliable, individualized, and dynamic surrogate of cardiovascular risk, synoptic for key biologic mechanisms, could shorten the path for drug development, enhance drug cost-effectiveness and improve patient outcomes. We used highly multiplexed proteomics to address these objectives, measuring about 5000 proteins in each of 32,130 archived plasma samples from 22,849 participants in nine clinical studies. We used machine learning to derive a 27-protein model predicting 4-year likelihood of myocardial infarction, stroke, heart failure, or death. The 27 proteins encompassed 10 biologic systems, and 12 were associated with relevant causal genetic traits. We independently validated results in 11,609 participants. Compared to a clinical model, the ratio of observed events in quintile 5 to quintile 1 was 6.7 for proteins versus 2.9 for the clinical model, AUCs (95% CI) were 0.73 (0.72 to 0.74) versus 0.64 (0.62 to 0.65), c-statistics were 0.71 (0.69 to 0.72) versus 0.62 (0.60 to 0.63), and the net reclassification index was +0.43. Adding the clinical model to the proteins only improved discrimination metrics by 0.01 to 0.02. Event rates in four predefined protein risk categories were 5.6, 11.2, 20.0, and 43.4% within 4 years; median time to event was 1.71 years. Protein predictions were directionally concordant with changed outcomes. Adverse risks were predicted for aging, approaching an event, anthracycline chemotherapy, diabetes, smoking, rheumatoid arthritis, cancer history, cardiovascular disease, high systolic blood pressure, and lipids. Reduced risks were predicted for weight loss and exenatide. The 27-protein model has potential as a "universal" surrogate end point for cardiovascular risk.

Plasma protein patterns as comprehensive indicators of health.

Proteins are effector molecules that mediate the functions of genes1,2 and modulate comorbidities3-10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12-16 coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check.

Flexible modeling of the hazard rate and treatment effects in long-term survival studies.

The effects of predictors on time to failure may be difficult to assess in cancer studies with longer follow-up, as the commonly used assumption of proportionality of hazards holding over an extended period is often questionable. Motivated by a long-term prostate cancer clinical trial, we contrast and compare four powerful methods for estimation of the hazard rate. These four methods allow for varying degrees of smoothness as well as covariates with effects that vary over time. We pay particular attention to an extended multiresolution hazard estimator, which is a flexible, semi-parametric, Bayesian method for joint estimation of predictor effects and the hazard rate. We compare the results of the extended multiresolution hazard model to three other commonly used, comparable models: Aalen's additive model, Kooperberg's hazard regression model, and an extended Cox model. Through simulations and the analysis of a large-scale randomized prostate cancer clinical trial, we use the different methods to examine patterns of biochemical failure and to estimate the time-varying effects of androgen deprivation therapy treatment and other covariates.

A multivariate cure model for left-censored and right-censored data with application to colorectal cancer screening patterns.

We develop a multivariate cure survival model to estimate lifetime patterns of colorectal cancer screening. Screening data cover long periods of time, with sparse observations for each person. Some events may occur before the study begins or after the study ends, so the data are both left-censored and right-censored, and some individuals are never screened (the 'cured' population). We propose a multivariate parametric cure model that can be used with left-censored and right-censored data. Our model allows for the estimation of the time to screening as well as the average number of times individuals will be screened. We calculate likelihood functions based on the observations for each subject using a distribution that accounts for within-subject correlation and estimate parameters using Markov chain Monte Carlo methods. We apply our methods to the estimation of lifetime colorectal cancer screening behavior in the SEER-Medicare data set. Copyright © 2016 John Wiley & Sons, Ltd.

Interfraction motion of the vaginal apex during postoperative intensity modulated radiation therapy: are we missing the target?

OBJECTIVE: This study aimed to evaluate changes in vaginal cuff position and rectal distention during whole pelvic intensity modulated radiation therapy using daily image guidance for patients with gynecologic malignancies. MATERIALS AND METHODS: We reviewed 145 daily images from 5 patients treated with intensity modulated radiation therapy after total abdominal hysterectomy for endometrial or cervical cancer. A fiducial marker was placed in the vaginal cuff tissue before computed tomographic simulation. The 2008 ASTRO consensus guidelines for delineation of clinical target volumes were used to deliver 45 to 50 Gy to the target structures. Daily megavoltage computed tomographic images were reviewed and changes in position of the fiducial marker as compared to the initial planning scan were recorded in the anterior-posterior (AP), lateral, and superior-inferior dimensions. Changes in rectal distention were also recorded. The position of the fiducial marker relative to the planning target volumes was reviewed on each daily image. RESULTS: The average shifts of the gold seed in the AP, lateral, and superior-inferior dimensions were 7 mm (range, 0-28 mm), 3 mm (range, 0-7 mm), and 2.9 mm (range, 0-12 mm), respectively. Distention of the rectum ranged from 20.5 to 60.1 mm and correlated with movement of the gold seed in the AP dimension (R = 0.53). For 2 patients, the fiducial marker was within 5 mm of the planning target volume margin on 8/40 treatments, or outside the planning target volume on 4/40 treatments. This did not significantly impact total delivered dose to the planning target volume. CONCLUSIONS: Daily image guidance confirms significant interfraction movement of the vaginal cuff tissue, which may exceed suggested guidelines for clinical target volume margins.

The prevalence, rate of progression, and treatment of elbow flexion contracture in children with brachial plexus birth palsy.

BACKGROUND: Elbow flexion contracture is a well-known complication of brachial plexus birth palsy that adversely affects upper-extremity function. The prevalence, risk factors, and rate of progression of elbow flexion contracture associated with brachial plexus birth palsy have not been established, and the effectiveness of nonoperative treatment involving nighttime splinting or serial casting has not been well studied. METHODS: The medical records of 319 patients with brachial plexus birth palsy who had been seen at our institution between 1992 and 2009 were retrospectively reviewed to identify patients with an elbow flexion contracture (≥10°). The chi-square test for trend and the Kaplan-Meier estimator were used to evaluate risk factors for contracture, including age, sex, and the extent of brachial plexus involvement. Longitudinal models were used to estimate the rate of contracture progression and the effectiveness of nonoperative treatment. RESULTS: An elbow flexion contracture was present in 48% (152) of the patients with brachial plexus birth palsy. The median age of onset was 5.1 years (range, 0.25 to 14.8 years). The contracture was ≥30° in 36% (fifty-four) of these 152 patients and was accompanied by a documented radial head dislocation in 6% (nine). The prevalence of contracture increased with increasing age (p < 0.001) but was not significantly associated with sex or with the extent of brachial plexus involvement. The magnitude of the contracture increased by 4.4% per year before treatment (p < 0.01). The magnitude of the contracture decreased by 31% when casting was performed (p < 0.01) but thereafter increased again at the same rate of 4.4% per year. The magnitude of the contracture did not improve when splinting was performed but the rate of increase thereafter decreased to <0.1% per year (p = 0.04). CONCLUSIONS: The prevalence of elbow flexion contracture in children with brachial plexus birth palsy may be greater than clinicians perceive. The prevalence increased with patient age but was not significantly affected by sex or by the extent of brachial plexus involvement. Serial casting may initially improve severe contractures, whereas nighttime splinting may prevent further progression of milder contractures.