Effects of procalcitonin on antimicrobial treatment decisions in patients with coronavirus disease 2019 (COVID-19).

OBJECTIVE: To describe the natural course of procalcitonin (PCT) in patients with coronavirus disease 2019 (COVID-19) and the correlation between PCT and antimicrobial prescribing to provide insight into best practices for PCT data utilization in antimicrobial stewardship in this population. DESIGN: Single-center, retrospective, observational study. SETTING: Michigan Medicine. PATIENTS: Inpatients aged ≥18 years hospitalized March 1, 2020, through October 31, 2021, who were positive for severe acute respiratory coronavirus virus 2 (SARS-CoV-2), with ≥1 PCT measurement. Exclusion criteria included antibiotics for nonpulmonary bacterial infection on admission, treatment with azithromycin only for chronic obstructive pulmonary disease (COPD) exacerbation, and pre-existing diagnosis of cystic fibrosis with positive respiratory cultures. METHODS: A structured query was used to extract data. For patients started on antibiotics, bacterial pneumonia (bPNA) was determined through chart review. Multivariable models were used to assess associations of PCT level and bPNA with antimicrobial use. RESULTS: Of 793 patients, 224 (28.2%) were initiated on antibiotics: 33 (14.7%) had proven or probable bPNA, 125 (55.8%) had possible bPNA, and 66 (29.5%) had no bPNA. Patients had a mean of 4.1 (SD, ±5.2) PCT measurements if receiving antibiotics versus a mean of 2.0 (SD, ±2.6) if not. Initial PCT level was highest for those with proven/probable bPNA and was associated with antibiotic initiation (odds ratio 95% confidence interval [CI], 1.17-1.30). Initial PCT (rate ratio [RR] 95% CI, 1.01-1.08), change in PCT over time (RR 95% CI, 1.01-1.05), and bPNA group (RR 95% CI, 1.23-1.84) were associated with antibiotic duration. CONCLUSIONS: PCT trends are associated with the decision to initiate antibiotics and duration of treatment, independent of bPNA status and comorbidities. Prospective studies are needed to determine whether PCT level can be used to safely make decisions regarding antibiotic treatment for COVID-19.

Surrogacy marker paradox measures in meta-analytic settings.

Because of the time and expense required to obtain clinical outcomes of interest, such as functional limitations or death, clinical trials often focus the effects of treatment on earlier and more easily obtained surrogate markers. Preliminary work to define surrogates focused on the fraction of a treatment effect "explained" by a marker in a regression model, but as notions of causality have been formalized in the statistical setting, formal definitions of high-quality surrogate markers have been developed in the causal inference framework, using either the "causal effect" or "causal association" settings. In the causal effect setting, high-quality surrogate markers have a large fraction of the total treatment effect explained by the effect of the treatment on the marker net of the treatment on the outcome. In the causal association setting, high-quality surrogate markers have large treatment effects on the outcome when there are large treatment effects on the marker, and small effects on the outcome when there are small effects on the marker. A particularly important feature of a surrogate marker is that the direction of a treatment effect be the same for both the marker and the outcome. Settings in which the marker and outcome are positively associated but the marker and outcome have beneficial and harmful or harmful and beneficial treatment effects, respectively, have been referred to as "surrogate paradoxes". If this outcome always occurs, it is not problematic; however, as correlations among the outcome, marker, and their treatment effects weaken, it may occur for some trials and not for others, leading to potentially incorrect conclusions, and real-life examples that shortened thousands of lives are unfortunately available. We propose measures for assessing the risk of the surrogate paradox using the meta-analytic causal association framework, which allows us to focus on the probability that a given treatment will yield treatment effect in different directions between the marker and the outcome, and to determine the size of a beneficial effect of the treatment on the marker required to minimize the risk of a harmful effect of the treatment on the outcome. We provide simulations and consider two applications.

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.

The very high premature mortality rate among active professional wrestlers is primarily due to cardiovascular disease.

PURPOSE: Recently, much media attention has been given to the premature deaths in professional wrestlers. Since no formal studies exist that have statistically examined the probability of premature mortality in professional wrestlers, we determined survival estimates for active wresters over the past quarter century to establish the factors contributing to the premature mortality of these individuals. METHODS: Data including cause of death was obtained from public records and wrestling publications in wrestlers who were active between January 1, 1985 and December 31, 2011. 557 males were considered consistently active wrestlers during this time period. 2007 published mortality rates from the Center for Disease Control were used to compare the general population to the wrestlers by age, BMI, time period, and cause of death. Survival estimates and Cox hazard regression models were fit to determine incident premature deaths and factors associated with lower survival. Cumulative incidence function (CIF) estimates given years wrestled was obtained using a competing risks model for cause of death. RESULTS: The mortality for all wrestlers over the 26-year study period was.007 deaths/total person-years or 708 per 100,000 per year, and 16% of deaths occurred below age 50 years. Among wrestlers, the leading cause of deaths based on CIF was cardiovascular-related (38%). For cardiovascular-related deaths, drug overdose-related deaths and cancer deaths, wrestler mortality rates were respectively 15.1, 122.7 and 6.4 times greater than those of males in the general population. Survival estimates from hazard models indicated that BMI is significantly associated with the hazard of death from total time wrestling (p<0.0001). CONCLUSION: Professional wrestlers are more likely to die prematurely from cardiovascular disease compared to the general population and morbidly obese wrestlers are especially at risk. Results from this study may be useful for professional wrestlers, as well as wellness policy and medical care implementation.

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.

Analytic morphometric assessment of patients undergoing colectomy for colon cancer.

BACKGROUND: Analytic morphometrics provides objective data that may better stratify risk. We investigated morphometrics and outcome among colon cancer patients. METHODS: An IRB-approved review identified 302 patients undergoing colectomy who had CT scans. These were processed to measure psoas area (PA), density (PD), subcutaneous fat (SFD), visceral fat (VF), and total body fat (TBF). Correlation with complications, recurrence, and survival were obtained by t-tests and linear regression models after adjusting for age and Charlson index. RESULTS: The best predictor of surgical complications was PD. PMH, Charlson, BMI, and age were not significant when PD was considered. SF area was the single best predictor of a wound infection. While all measures of obesity correlated with outcome, TBF was most predictive. Final multivariate Cox models for survival included age, Charlson score, nodal positivity, and TBF. CONCLUSIONS: Analytic morphometric analysis provided objective data that stratified complications and outcome better than age, BMI, or co-morbidities.

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.

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 patient's 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.