Anna Conlon

Analytic morphometric assessment of patients undergoing colectomy for colon cancer

Analytic morphometrics provides objective data that may better stratify risk. We investigated morphometrics and outcome among colon cancer patients.

Multi-institutional Prospective Evaluation of Bowel Quality of Life After Prostate External Beam Radiation Therapy Identifies Patient and Treatment Factors Associated With Patient-Reported Outcomes: The PROSTQA Experience

PURPOSE To evaluate patients treated with external beam radiation therapy as part of the multicenter Prostate Cancer Outcomes and Satisfaction with Treatment Quality Assessment (PROSTQA), to identify factors associated with posttreatment patient-reported bowel health-related quality of life (HRQOL). METHODS AND MATERIALS Pretreatment characteristics and treatment details among 292 men were evaluated using a general linear mixed model for their association with measured HRQOL by the Expanded Prostate Cancer Index Composite instrument through 2 years after enrollment. RESULTS Bowel HRQOL had a median score of 100 (interquartile range 91.7-100) pretreatment and 95.8 (interquartile range 83.3-100) at 2 years, representing new moderate/big problems in 11% for urgency, 7% for frequency, 4% for bloody stools, and 8% for an overall bowel problems. Baseline bowel score was the strongest predictor for all 2-year endpoints. In multivariable models, a volume of rectum ≥25% treated to 70 Gy (V70) yielded a clinically significant 9.3-point lower bowel score (95% confidence interval [CI] 16.8-1.7, P=.015) and predicted increased risks for moderate to big fecal incontinence (P=.0008). No other radiation therapy treatment-related variables influenced moderate to big changes in rectal HRQOL. However, on multivariate analyses V70 ≥25% was associated with increases in small, moderate, or big problems with the following: incontinence (3.9-fold; 95% CI 1.1-13.4, P=.03), rectal bleeding (3.6-fold; 95% CI 1.3-10.2, P=.018), and bowel urgency (2.9-fold; 95% CI 1.1-7.6, P=.026). Aspirin use correlated with a clinically significant 4.7-point lower bowel summary score (95% CI 9.0-0.4, P=.03) and an increase in small, moderate, or big problems with bloody stools (2.8-fold; 95% CI 1.2-6.4, P=.018). Intensity modulated radiation therapy was associated with higher radiation therapy doses to the prostate and lower doses to the rectum but did not independently correlate with bowel HRQOL. CONCLUSION After contemporary dose-escalated external beam radiation therapy up to 11% of patients have newly identified moderate/big problems with bowel HRQOL 2 years after treatment. Bowel HRQOL is related to baseline function, rectal V70, and aspirin use. Finally, our findings validate the commonly utilized cut-point of rectal V70 ≥25% as having significant impact on patient-reported outcomes.

Dose to the inferior rectum is strongly associated with patient reported bowel quality of life after radiation therapy for prostate cancer.

PURPOSE To evaluate rectal dose and post-treatment patient-reported bowel quality of life (QOL) following radiation therapy for prostate cancer. METHODS Patient-reported QOL was measured at baseline and 2-years via the expanded prostate cancer index composite (EPIC) for 90 patients. Linear regression modeling was performed using the baseline score for the QUANTEC normal tissue complication probability model and dose volume histogram (DVH) parameters for the whole and segmented rectum (superior, middle, and inferior). RESULTS At 2-years the mean summary score declined from a baseline of 96.0-91.8. The median volume of rectum treated to ≥70 Gy (V70) was 11.7% for the whole rectum and 7.0%, 24.4%, and 1.3% for the inferior, middle, and superior rectum, respectively. Mean dose to the whole and inferior rectum correlated with declines in bowel QOL while dose to the mid and superior rectum did not. Low (V25-V40), intermediate (V50-V60) and high (V70-V80) doses to the inferior rectum influenced bleeding, incontinence, urgency, and overall bowel problems. Only the highest dose (V80) to the mid-rectum correlated with rectal bleeding and overall bowel problems. CONCLUSIONS Segmental DVH analysis of the rectum reveals associations between bowel QOL and inferior rectal dose that could significantly influence radiation planning and prognostic models.

Surrogacy assessment using principal stratification when surrogate and outcome measures are multivariate normal

In clinical trials, a surrogate outcome variable (S) can be measured before the outcome of interest (T) and may provide early information regarding the treatment (Z) effect on T. Using the principal surrogacy framework introduced by Frangakis and Rubin (2002. Principal stratification in causal inference. Biometrics 58, 21-29), we consider an approach that has a causal interpretation and develop a Bayesian estimation strategy for surrogate validation when the joint distribution of potential surrogate and outcome measures is multivariate normal. From the joint conditional distribution of the potential outcomes of T, given the potential outcomes of S, we propose surrogacy validation measures from this model. As the model is not fully identifiable from the data, we propose some reasonable prior distributions and assumptions that can be placed on weakly identified parameters to aid in estimation. We explore the relationship between our surrogacy measures and the surrogacy measures proposed by Prentice (1989. Surrogate endpoints in clinical trials: definition and operational criteria. Statistics in Medicine 8, 431-440). The method is applied to data from a macular degeneration study and an ovarian cancer study.

Multi‐state models for colon cancer recurrence and death with a cured fraction

In cancer clinical trials, patients often experience a recurrence of disease prior to the outcome of interest, overall survival. Additionally, for many cancers, there is a cured fraction of the population who will never experience a recurrence. There is often interest in how different covariates affect the probability of being cured of disease and the time to recurrence, time to death, and time to death after recurrence. We propose a multi-state Markov model with an incorporated cured fraction to jointly model recurrence and death in colon cancer. A Bayesian estimation strategy is used to obtain parameter estimates. The model can be used to assess how individual covariates affect the probability of being cured and each of the transition rates. Checks for the adequacy of the model fit and for the functional forms of covariates are explored. The methods are applied to data from 12 randomized trials in colon cancer, where we show common effects of specific covariates across the trials.

A Model to Predict Central-Line–Associated Bloodstream Infection Among Patients With Peripherally Inserted Central Catheters: The MPC Score

BACKGROUND Peripherally inserted central catheters (PICCs) are associated with central-line-associated bloodstream infections (CLABSIs). However, no tools to predict risk of PICC-CLABSI have been developed. OBJECTIVE To operationalize or prioritize CLABSI risk factors when making decisions regarding the use of PICCs using a risk model to estimate an individuals risk of PICC-CLABSI prior to device placement. METHODS Using data from the Michigan Hospital Medicine Safety consortium, patients that experienced PICC-CLABSI between January 2013 and October 2016 were identified. A Cox proportional hazards model with robust sandwich standard error estimates was then used to identify factors associated with PICC-CLABSI. Based on regression coefficients, points were assigned to each predictor and summed for each patient to create the Michigan PICC-CLABSI (MPC) score. The predictive performance of the score was assessed using time-dependent area-under-the-curve (AUC) values. RESULTS Of 23,088 patients that received PICCs during the study period, 249 patients (1.1%) developed a CLABSI. Significant risk factors associated with PICC-CLABSI included hematological cancer (3 points), CLABSI within 3 months of PICC insertion (2 points), multilumen PICC (2 points), solid cancers with ongoing chemotherapy (2 points), receipt of total parenteral nutrition (TPN) through the PICC (1 point), and presence of another central venous catheter (CVC) at the time of PICC placement (1 point). The MPC score was significantly associated with risk of CLABSI (P<.0001). For every point increase, the hazard ratio of CLABSI increased by 1.63 (95% confidence interval, 1.56-1.71). The area under the receiver-operating-characteristics curve was 0.67 to 0.77 for PICC dwell times of 6 to 40 days, which indicates good model calibration. CONCLUSION The MPC score offers a novel way to inform decisions regarding PICC use, surveillance of high-risk cohorts, and utility of blood cultures when PICC-CLABSI is suspected. Future studies validating the score are necessary. Infect Control Hosp Epidemiol 2017;38:1155-1166.

Using cure models and multiple imputation to utilize recurrence as an auxiliary variable for overall survival

Background Intermediate outcome variables can often be used as auxiliary variables for the true outcome of interest in randomized clinical trials. For many cancers, time to recurrence is an informative marker in predicting a patients overall survival outcome and could provide auxiliary information for the analysis of survival times. Purpose To investigate whether models linking recurrence and death combined with a multiple imputation procedure for censored observations can result in efficiency gains in the estimation of treatment effects and be used to shorten trial lengths. Methods Recurrence and death times are modeled using data from 12 trials in colorectal cancer. Multiple imputation is used as a strategy for handling missing values arising from censoring. The imputation procedure uses a cure model for time to recurrence and a time-dependent Weibull proportional hazards model for time to death. Recurrence times are imputed, and then death times are imputed conditionally on recurrence times. To illustrate these methods, trials are artificially censored 2 years after the last accrual, the imputation procedure implemented, and a log-rank test and Cox model used to analyze and compare these new data with the original data. Results The results show modest, but consistent gains in efficiency in the analysis using the auxiliary information in recurrence times. Comparison of analyses show the treatment effect estimates and log-rank test results from the 2-year censored imputed data to be in between the estimates from the original data and the artificially censored data, indicating that the procedure was able to recover some of the lost information due to censoring. Limitations The models used are all fully parametric, requiring distributional assumptions of the data. Conclusions The proposed models may be useful in improving the efficiency in estimation of treatment effects in cancer trials and shortening trial length.

The Michigan Risk Score to predict peripherally inserted central catheter-associated thrombosis

Essentials How best to quantify thrombosis risk with peripherally inserted central catheters (PICC) is unknown. Data from a registry were used to develop the Michigan Risk Score (MRS) for PICC thrombosis. Five risk factors were associated with PICC thrombosis and used to develop a risk score. MRS was predictive of the risk of PICC thrombosis and can be useful in clinical practice.

Surrogacy assessment using principal stratification with multivariate normal and Gaussian copula models

Background The validation of intermediate markers as surrogate markers (S) for the true outcome of interest (T) in clinical trials offers the possibility for trials to be run more quickly and cheaply by using the surrogate endpoint in place of the true endpoint. Purpose Working within a principal stratification framework, we propose causal quantities to evaluate surrogacy using a Gaussian copula model for an ordinal surrogate and time-to-event final outcome. The methods are applied to data from four colorectal cancer clinical trials, where S is tumor response and T is overall survival. Methods For the Gaussian copula model, a Bayesian estimation strategy is used and, as some parameters are not identifiable from the data, we explore the use of informative priors that are consistent with reasonable assumptions in the surrogate marker setting to aid in estimation. Results While there is some bias in the estimation of the surrogacy quantities of interest, the estimation procedure does reasonably well at distinguishing between poor and good surrogate markers. Limitations Some of the parameters of the proposed model are not identifiable from the data, and therefore, assumptions must be made in order to aid in their estimation. Conclusions The proposed quantities can be used in combination to provide evidence about the validity of S as a surrogate marker for T.

Improving efficiency in clinical trials using auxiliary information: Application of a multi-state cure model

In clinical trials, an intermediate marker measured after randomization can often provide early information about the treatment effect on the final outcome of interest. We explore the use of recurrence time as an auxiliary variable for estimating the treatment effect on overall survival in phase three randomized trials of colon cancer. A multi-state model with an incorporated cured fraction for recurrence is used to jointly model time to recurrence and time to death. We explore different ways in which the information about recurrence time and the assumptions in the model can lead to improved efficiency. Estimates of overall survival and disease-free survival can be derived directly from the model with efficiency gains obtained as compared to Kaplan-Meier estimates. Alternatively, efficiency gains can be achieved by using the model in a weaker way in a multiple imputation procedure, which imputes death times for censored subjects. By using the joint model, recurrence is used as an auxiliary variable in predicting survival times. We demonstrate the potential use of the proposed methods in shortening the length of a trial and reducing sample sizes.