Long-term major adverse liver outcomes in 1,260 patients with non-cirrhotic NAFLD.

Background & Aims: Long-term studies of the prognosis of NAFLD are scarce. Here, we investigated the risk of major adverse liver outcomes (MALO) in a large cohort of patients with NAFLD. Methods: We conducted a cohort study with data from Swedish university hospitals. Patients (n = 1,260) with NAFLD without cirrhosis were diagnosed through biopsy or radiology, and had fibrosis estimated through vibration-controlled transient elastography, biopsy, or FIB-4 score between 1974 and 2020 and followed up through 2020. Each patient was matched on age, sex, and municipality with up to 10 reference individuals from the general population (n = 12,529). MALO were ascertained from Swedish national registers. The rate of events was estimated by Cox regression. Results: MALO occurred in 111 (8.8%, incidence rate = 5.9/1,000 person-years) patients with NAFLD and 197 (1.6%, incidence rate = 1.0/1,000 person-years) reference individuals during a median follow up of 13 years. The rate of MALO was higher in patients with NAFLD (hazard ratio = 6.6; 95% CI = 5.2-8.5). The risk of MALO was highly associated with the stage of fibrosis at diagnosis. In the biopsy subcohort (72% of total sample), there was no difference in risk between patients with and without non-alcoholic steatohepatitis. The 20-year cumulative incidences of MALO were 2% for the reference population, 3% for patients with F0, and 35% for F3. Prognostic information from biopsy was comparable to FIB-4 (C-indices around 0.73 vs. 0.72 at 10 years). Conclusions: This study provides updated information on the natural history of NAFLD, showing a high rate of progression to cirrhosis in F3 and a similar prognostic capacity of non-invasive tests to liver biopsy. Impact and implications: Several implications for clinical care and future research may be noted based on these results. First, the risk estimates for cirrhosis development are important when communicating risk to patients and deciding on clinical monitoring and treatment. Estimates can also be used in updated health-economic evaluations, and for regulatory agencies. Second, our results again highlight the low predictive information obtained from ascertaining NASHstatus by histology and call for more objective means by which to define NASH. Such methods may include artificial intelligence-supported digital pathology. We highlight that NASH is most likely the causal factor for fibrosis progression in NAFLD, but the subjective definition makes the prognostic value of a histological NASH diagnosis of limited value. Third, the finding that prognostic information from biopsy and the very simple Fibrosis-4 score were comparable is important as it may lead to fewer biopsies and further move the field towards non-invasive means by which to define fibrosis and, importantly, use non-invasive tests as outcomes in clinical trials. However, all modalities had modest discriminatory capacity and new risk stratification systems are needed in NAFLD. Repeated measures of non-invasive scores may be a potential solution.

Generate Analysis-Ready Data for Real-world Evidence: Tutorial for Harnessing Electronic Health Records With Advanced Informatic Technologies.

Although randomized controlled trials (RCTs) are the gold standard for establishing the efficacy and safety of a medical treatment, real-world evidence (RWE) generated from real-world data has been vital in postapproval monitoring and is being promoted for the regulatory process of experimental therapies. An emerging source of real-world data is electronic health records (EHRs), which contain detailed information on patient care in both structured (eg, diagnosis codes) and unstructured (eg, clinical notes and images) forms. Despite the granularity of the data available in EHRs, the critical variables required to reliably assess the relationship between a treatment and clinical outcome are challenging to extract. To address this fundamental challenge and accelerate the reliable use of EHRs for RWE, we introduce an integrated data curation and modeling pipeline consisting of 4 modules that leverage recent advances in natural language processing, computational phenotyping, and causal modeling techniques with noisy data. Module 1 consists of techniques for data harmonization. We use natural language processing to recognize clinical variables from RCT design documents and map the extracted variables to EHR features with description matching and knowledge networks. Module 2 then develops techniques for cohort construction using advanced phenotyping algorithms to both identify patients with diseases of interest and define the treatment arms. Module 3 introduces methods for variable curation, including a list of existing tools to extract baseline variables from different sources (eg, codified, free text, and medical imaging) and end points of various types (eg, death, binary, temporal, and numerical). Finally, module 4 presents validation and robust modeling methods, and we propose a strategy to create gold-standard labels for EHR variables of interest to validate data curation quality and perform subsequent causal modeling for RWE. In addition to the workflow proposed in our pipeline, we also develop a reporting guideline for RWE that covers the necessary information to facilitate transparent reporting and reproducibility of results. Moreover, our pipeline is highly data driven, enhancing study data with a rich variety of publicly available information and knowledge sources. We also showcase our pipeline and provide guidance on the deployment of relevant tools by revisiting the emulation of the Clinical Outcomes of Surgical Therapy Study Group Trial on laparoscopy-assisted colectomy versus open colectomy in patients with early-stage colon cancer. We also draw on existing literature on EHR emulation of RCTs together with our own studies with the Mass General Brigham EHR.

Confounding adjustment in the analysis of augmented randomized controlled trial with hybrid control arm.

The augmented randomized controlled trial (RCT) with hybrid control arm includes a randomized treatment group (RT), a smaller randomized control group (RC), and a large synthetic control (SC) group from real-world data. This kind of trial is useful when there is logistics and ethics hurdle to conduct a fully powered RCT with equal allocation, or when it is necessary to increase the power of the RCT by incorporating real-world data. A difficulty in the analysis of augmented RCT is that the SC and RC may be systematically different in the distribution of observed and unmeasured confounding factors, causing bias when the two control groups are analyzed together as hybrid controls. We propose to use propensity score (PS) analysis to balance the observed confounders between SC and RC. The possible bias caused by unmeasured confounders can be estimated and tested by analyzing propensity score adjusted outcomes from SC and RC. We also propose a partial bias correction (PBC) procedure to reduce bias from unmeasured confounding. Extensive simulation studies show that the proposed PS + PBC procedures can improve the efficiency and statistical power by effectively incorporating the SC into the RCT data analysis, while still control the estimation bias and Type I error inflation that might arise from unmeasured confounding. We illustrate the proposed statistical procedures with data from an augmented RCT in oncology.

Temporal Trends in Clinical Evidence of 5-Year Survival Within Electronic Health Records Among Patients With Early-Stage Colon Cancer Managed With Laparoscopy-Assisted Colectomy vs Open Colectomy.

Importance: Temporal shifts in clinical knowledge and practice need to be adjusted for in treatment outcome assessment in clinical evidence. Objective: To use electronic health record (EHR) data to (1) assess the temporal trends in treatment decisions and patient outcomes and (2) emulate a randomized clinical trial (RCT) using EHR data with proper adjustment for temporal trends. Design, Setting, and Participants: The Clinical Outcomes of Surgical Therapy (COST) Study Group Trial assessing overall survival of patients with stages I to III early-stage colon cancer was chosen as the target trial. The RCT was emulated using EHR data of patients from a single health care system cohort who underwent colectomy for early-stage colon cancer from January 1, 2006, to December 31, 2017, and were followed up to January 1, 2020, from Mass General Brigham. Analyses were conducted from December 2, 2019, to January 24, 2022. Exposures: Laparoscopy-assisted colectomy (LAC) vs open colectomy (OC). Main Outcomes and Measures: The primary outcome was 5-year overall survival. To address confounding in the emulation, pretreatment variables were selected and adjusted. The temporal trends were adjusted by stratification of the calendar year when the colectomies were performed with cotraining across strata. Results: A total of 943 patients met key RCT eligibility criteria in the EHR emulation cohort, including 518 undergoing LAC (median age, 63 [range, 20-95] years; 268 [52%] women; 121 [23%] with stage I, 165 [32%] with stage II, and 232 [45%] with stage III cancer; 32 [6%] with colon adhesion; 278 [54%] with right-sided colon cancer; 18 [3%] with left-sided colon cancer; and 222 [43%] with sigmoid colon cancer) and 425 undergoing OC (median age, 65 [range, 28-99] years; 223 [52%] women; 61 [14%] with stage I, 153 [36%] with stage II, and 211 [50%] with stage III cancer; 39 [9%] with colon adhesion; 202 [47%] with right-sided colon cancer; 39 [9%] with left-sided colon cancer; and 201 [47%] with sigmoid colon cancer). Tests for temporal trends in treatment assignment (χ2 = 60.3; P < .001) and overall survival (χ2 = 137.2; P < .001) were significant. The adjusted EHR emulation reached the same conclusion as the RCT: LAC is not inferior to OC in overall survival rate with risk difference at 5 years of -0.007 (95% CI, -0.070 to 0.057). The results were consistent for stratified analysis within each temporal period. Conclusions and Relevance: These findings suggest that confounding bias from temporal trends should be considered when conducting clinical evidence studies with long time spans. Stratification of calendar time and cotraining of models is one solution. With proper adjustment, clinical evidence may supplement RCTs in the assessment of treatment outcome over time.

Propensity score-integrated Bayesian prior approaches for augmented control designs: a simulation study.

Drug development can be costly, and the availability of clinical trial participants may be limited either due to the disease setting (rare or pediatric diseases) or due to many sponsors evaluating multiple drugs or combinations in the same patient population. To maximize resource utilization, sponsors may leverage patient-level control data from historical trials. However, in a study with no control arm, it is impossible to evaluate if the historical controls are an appropriate comparator for the current study. Here, instead of conducting a single-arm trial and relying solely on historical controls, we evaluate the situation where a minimal number of patients are enrolled into a control arm, which is augmented by borrowing historical control data. Propensity score (PS) methods are commonly used to minimize bias for non-randomized data. In addition, Bayesian information borrowing with PS adjustments has been proposed when it may not be reasonable to include all available historical data. This paper proposes using PS adjustment integrated with Bayesian commensurate priors to adaptively borrow information. We then evaluate the performance of different PS adjustment methods and different Bayesian priors for augmented control using simulation studies to help inform the design of future trials. In general, we find that propensity weighting or matching combined with the commensurate prior yield reasonable statistical properties across a range of scenarios. Finally, our proposed methods are applied to a real trial with a binary outcome.Abbreviations: PS: propensity score; IPTW: inverse probability of treatment weighting; ATT: average treatment effect on those who received treatment; RCT: randomized controlled trial; CDD: covariate distribution difference; ESS: effective sample size.

Replication of Oncology Randomized Trial Results using Swedish Registry Real World-Data: A Feasibility Study.

Nationwide healthcare registries are potential important real-world data (RWD) sources for assessing drug effectiveness in oncology. However, it is unclear whether registry-derived RWD are suitable for clinical development. In this study, we replicate results from the comparator arm of two previously published oncology randomized controlled trials (RCTs) using RWD from Swedish nationwide healthcare registries. For replication 1, the RCT included 553 patients and the RWD included 283 patients treated with sorafenib for advanced hepatocellular cancer. The median overall survival (OS) was 11.2 (95% confidence interval (CI): 10.1-13.2) months in the RCT and 8.2 (95% CI: 7.0-9.9) months in the RWD, unadjusted hazard ratio (HR) 0.75 (95% CI: 0.63-0.88). For time-to-treatment discontinuation (TTD), the HR was 1.00 (95% CI: 0.87-1.16). For replication 2, the RCT included 154 patients and the RWD included 704 patients treated with melphalan, prednisone, and thalidomide for untreated multiple myeloma. The median OS was 52.6 (95% CI: 40-not applicable) months in the RCT and 36.9 (95% CI: 33.8-40.5) months in the RWD, unadjusted HR 0.67 (95% CI: 0.51-0.87). For TTD, the HR was 0.89 (95% CI: 0.74-1.06). The results were similar when applying various propensity-based confounding adjustments. In conclusion, OS was shorter in the RWD, whereas TTD was similar. Importantly, the data necessary (ex: eligibility criteria and baseline confounders) for replicating RCTs was mostly not available and these results further underscore the importance of developing frameworks for capturing relevant patient-level RWD for clinical and regulatory decision making in oncology.

Augmenting Real-World Data Through Modeling Key Clinical Trial Eligibility Criteria: An Example of Patients With Non-small-Cell Lung Cancer Treated With Pembrolizumab.

PURPOSE: To compare and characterize baseline characteristics and overall survival (OS) differences by key oncology eligibility criteria for real-world patients from the Flatiron Health database with advanced non-small-cell lung cancer (NSCLC) who received pembrolizumab monotherapy. METHODS: Real world data (RWD) were from the Flatiron Health advanced NSCLC database and include patients who initiated pembrolizumab monotherapy (first, second, or third line of therapy) by November 30, 2019. At the data cutoff (May 31, 2020), the median survival follow-up time was 8.4 months. Eligible patients satisfy the criteria of Eastern Cooperative Oncology Group performance status of 0/1 and laboratory values indicative of adequate organ function. RWD were analyzed for all patients and patients with a programmed cell death ligand-1 tumor proportion score ≥ 1%. Patients were divided into three categories: ineligible, eligible, and unknown (who satisfy all observed criteria, with at least one missing). An augmented population was also formed, which combines the latter two groups through a propensity-based adjustment. RESULTS: At the data cutoff, N = 3,877 patients with NSCLC received pembrolizumab monotherapy (1L = 2,682, 2L = 946, and 3L = 249). OS was consistently lower for the ineligible with similar survival for the eligible and augmented. Among all patients, the median OS in months (95% CI) was 8.2 (7.5 to 9.6), 16.3 (14.5 to 18.4), 16.4 (15.1 to 19.3), and 16.8 (15.6 to 18.5) for the ineligible (47%, n = 1,827), unknown (27%, n = 1,045), eligible (26%, n = 1,005), and augmented, respectively. The results were similar for patients with a programmed cell death ligand-1 tumor proportion score ≥ 1%. CONCLUSION: Real-world patients who received pembrolizumab monotherapy and meet key clinical eligibility criteria exhibited similar baseline characteristics and OS profiles as the unknown and augmented patient groups. Population augmentation is a feasible approach for improving the power of RWD analysis.

Overall Survival With Second-Line Pembrolizumab in Patients With Non-Small-Cell Lung Cancer: Randomized Phase III Clinical Trial Versus Propensity-Adjusted Real-World Data.

PURPOSE: To compare and characterize overall survival (OS) differences between clinical trial data from the KEYNOTE-010 trial and real-world data (RWD) from the Flatiron Health database in patients with programmed death ligand 1 (PD-L1)-expressing advanced non-small-cell lung cancer (NSCLC) who received second-line pembrolizumab monotherapy. METHODS: Clinical trial data were from the randomized phase II/III KEYNOTE-010 trial that enrolled patients from August 28, 2013, to February 27, 2015. At data cutoff for KEYNOTE-010, the median survival follow-up time for pembrolizumab patients was 11.2 months. RWD were from Flatiron Health advanced NSCLC database and included patients who initiated second-line pembrolizumab from January 26, 2015, to February 28, 2019. At data cutoff for Flatiron, the median survival follow-up time for pembrolizumab-treated patients was 6.1 months. Clinical trial data from KEYNOTE-010 and RWD from Flatiron were analyzed without adjustment, with propensity adjustment, and filtered per the main KEYNOTE-010 eligibility criteria (EC) of histologically/cytologically confirmed PD-L1-positive NSCLC, Eastern Cooperative Oncology Group performance status of 0/1, no prior therapy with docetaxel for NSCLC, and laboratory values indicative of adequate organ function in addition to prior line of therapy requirements. RESULTS: Among 243 patients from KEYNOTE-010 and 782 from Flatiron, median age was 63 v 68 years, and 64% v 54% were male, respectively. OS data from KEYNOTE-010 and Flatiron were similar without any adjustment (n = 782; hazard ratio [HR], 0.96; 95% CI, 0.80 to 1.15) and after both filtering and propensity adjustment (n = 221; HR, 0.99; 95% CI, 0.73 to 1.34). CONCLUSION: Without any adjustment, as well as after applying similar EC and appropriate statistical methods, RWD demonstrated similar effectiveness for pembrolizumab in second-line NSCLC as observed in randomized clinical trials.

Oncology phase II proof-of-concept studies with multiple targets: Randomized controlled trial or single arm?

For oncology drug development, phase II proof-of-concept studies have played a key role in determining whether or not to advance to a confirmatory phase III trial. With the increasing number of immunotherapies, efficient design strategies are crucial in moving successful drugs quickly to market. Our research examines drug development decision making under the framework of maximizing resource investment, characterized by benefit cost ratios (BCRs). In general, benefit represents the likelihood that a drug is successful, and cost is characterized by the risk adjusted total sample size of the phases II and III studies. Phase III studies often include a futility interim analysis; this sequential component can also be incorporated into BCRs. Under this framework, multiple scenarios can be considered. For example, for a given drug and cancer indication, BCRs can yield insights into whether to use a randomized control trial or a single-arm study. Importantly, any uncertainty in historical control estimates that are used to benchmark single-arm studies can be explicitly incorporated into BCRs. More complex scenarios, such as restricted resources or multiple potential cancer indications, can also be examined. Overall, BCR analyses indicate that single-arm trials are favored for proof-of-concept trials when there is low uncertainty in historical control data and smaller phase III sample sizes. Otherwise, especially if the most likely to succeed tumor indication can be identified, randomized controlled trials may be a better option. While the findings are consistent with intuition, we provide a more objective approach.

Are tumor size changes predictive of survival for checkpoint blockade based immunotherapy in metastatic melanoma?

BACKGROUND: In oncology clinical development, objective response rate, disease control rate and early tumor size changes are commonly used as efficacy metrics for early decision-making. However, for immunotherapy trials, it is unclear whether these early efficacy metrics are still predictive of long-term clinical benefit such as overall survival. The goal of this paper is to identify appropriate early efficacy metrics predictive of overall survival for immunotherapy trials. METHODS: Based on several checkpoint blockade based immunotherapy studies in metastatic melanoma, we evaluated the predictive value of early tumor size changes and RECIST-based efficacy metrics at various time points on overall survival. The cut-off values for tumor size changes to predict survival were explored via tree based recursive partitioning and validated by external data. Sensitivity analyses were performed for the cut-offs. RESULTS: The continuous tumor size change metric and RECIST-based trichotomized response metric at different landmark time points were found to be statistically significantly associated with overall survival. The predictive values were higher at Week 12 and 18 than those at Week 24. The percentage of tumor size changes appeared to have comparable or lower predictive values than the RECIST-based trichotomized metric, and a cut-off of approximately 10% tumor reduction appeared to be reasonable for predicting survival. CONCLUSIONS: An approximate 10% tumor reduction may be a reasonable cut-off for early decision-making while the RECIST-based efficacy metric remains the primary tool. Early landmark analysis is especially useful for decision making when accrual is fast. Composite response rate (utilizing different weights for PR/CR and SD) may be worth further investigation. TRIAL REGISTRATION: Clinical trials gov, NCT01295827 , Registered February 15, 2011; NCT01704287 , Registered October 11, 2012; NCT01866319 , Registered May 31, 2013.

Efficient baseline utilization for incomplete block crossover clinical trials.

Incomplete block crossover trials with period-specific baseline and post-baseline (outcome) measures for each subject are often used in clinical drug development; without loss of generality, we focus on the three-treatment two-period ( 3×2 ) crossover. Data from such trials are commonly analyzed using a mixed effects model with indicator terms for treatment and period, and an unstructured covariance matrix for the vector of intra-subject measurements. It is well-known that treatment effect estimates from this analysis are complex functions of both within-subject and between-subject treatment contrasts. We caution that the associated type I error rate and power for hypothesis testing can be non-trivially influenced by how the baselines are utilized. Specifically, the mixed effects analysis which uses change from baseline as the dependent variable is shown to consistently underperform corresponding analyses in which the outcome is the dependent variable and linear combinations of the baselines are used as period-specific and/or period-invariant covariates. A simpler fixed effects analysis of covariance involving only within-subject contrasts is also described for small sample situations in which the mixed effects analyses can suffer from increased type I error rates. Theoretical insights, simulation results and an illustrative example with real data are used to develop the main points.

Oral Antibiotic Exposure and Kidney Stone Disease.

Background Although intestinal and urinary microbiome perturbations are associated with nephrolithiasis, whether antibiotics are a risk factor for this condition remains unknown.Methods We determined the association between 12 classes of oral antibiotics and nephrolithiasis in a population-based, case-control study nested within 641 general practices providing electronic health record data for >13 million children and adults from 1994 to 2015 in the United Kingdom. We used incidence density sampling to match 25,981 patients with nephrolithiasis to 259,797 controls by age, sex, and practice at date of diagnosis (index date). Conditional logistic regression models were adjusted for the rate of health care encounters, comorbidities, urinary tract infections, and use of thiazide and loop diuretics, proton-pump inhibitors, and statins.Results Exposure to any of five different antibiotic classes 3-12 months before index date was associated with nephrolithiasis. The adjusted odds ratio (95% confidence interval) was 2.33 (2.19 to 2.48) for sulfas, 1.88 (1.75 to 2.01) for cephalosporins, 1.67 (1.54 to 1.81) for fluoroquinolones, 1.70 (1.55 to 1.88) for nitrofurantoin/methenamine, and 1.27 (1.18 to 1.36) for broad-spectrum penicillins. In exploratory analyses, the magnitude of associations was greatest for exposure at younger ages (P<0.001) and 3-6 months before index date (P<0.001), with all but broad-spectrum penicillins remaining statistically significant 3-5 years from exposure.Conclusions Oral antibiotics associated with increased odds of nephrolithiasis, with the greatest odds for recent exposure and exposure at younger age. These results have implications for disease pathogenesis and the rising incidence of nephrolithiasis, particularly among children.

A Case-Crossover Study of Urological Chronic Pelvic Pain Syndrome Flare Triggers in the MAPP Research Network.

PURPOSE: Although many factors have been proposed to trigger symptom exacerbations (flares) in patients with interstitial cystitis/bladder pain syndrome and chronic prostatitis/chronic pelvic pain syndrome, few studies have investigated these factors empirically. Therefore, we embedded a case-crossover study in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain longitudinal study to evaluate a range of patient reported triggers. MATERIALS AND METHODS: We assessed exposure to proposed triggers, including diet, physical activities, sedentary behaviors, stress, sexual activities, infection-like symptoms and allergies, by questionnaire a maximum of 3 times when participants reported flares and at 3 randomly selected times. We compared participant preflare to nonflare exposures by conditional logistic regression. RESULTS: In our full analytical sample of 292 participants only 2 factors, including recent sexual activity (OR 1.44, 95% CI 1.06-1.96) and urinary tract infection symptoms (OR 3.39, 95% CI 2.02-5.68), which may overlap with those of flares, were associated with flare onset. On subanalyses restricted to flares with specific suspected triggers additional positive associations were observed for some factors such as certain dietary factors, abdominal muscle exercises, and vaginal infection-like symptoms and fever, but not for other factors (eg stress). CONCLUSIONS: Except for sexual activity our findings suggest that patient reported triggers may be individual or group specific, or they may not contribute to flares. These findings suggest caution in following rigid, global flare prevention strategies and support additional research to develop evidence-based strategies.

Variability in measures of mineral metabolism in children on hemodialysis: impact on clinical decision-making.

BACKGROUND: Variability in measures of mineral metabolism has not been studied in pediatric end stage kidney disease. We sought to determine the intra-individual variability in measures of mineral metabolism in children on hemodialysis (HD) and its impact on clinical decision-making. METHODS: We conducted a prospective single-center study of children (3.6-17.3 years old) on chronic HD. Serial twice weekly measures of serum calcium, phosphate and intact parathyroid hormone (PTH), as well as weekly measures of fibroblast growth factor 23 (FGF23) and vitamin D metabolites, were obtained over a 12-week period in 10 children. Samples (n = 226) were assayed in a single batch at the end of the study. RESULTS: The median intra-individual coefficient of variation (CV) calculated by 4-week blocks was 5.1-6.5% for calcium, 9.5-14.9% for phosphate and 32.7-33.4% for PTH. The median overall CV for FGF23 was 44.4%. Using the first value of each block as a reference, subsequent values would dictate a discrepant management decision 33-56%, 19-28%, and 30-33% of the time for calcium, phosphate, and PTH, respectively. Adjusting for sex and age, most of the variability in phosphate and PTH was attributable to within-participant variability. For calcium, 49% of the variability was attributable to day of blood collection (Monday vs. Friday). The median (range) of an individual participant's values within clinical target ranges was 55% (26-86%) for calcium, 58% (0-96%) for phosphate, and 21% (0-64%) for PTH. CONCLUSIONS: There is considerable intra-individual variability in measures of mineral metabolism that serve as surrogate markers for bone health in children on HD. Within a 4-week period, at least 20-30% of measures would dictate a discrepant decision from the referent measure of that month. These findings have important implications for clinical decision-making and underscore the need to base therapeutic decisions on trends rather than single measurements.

Risk of Urolithiasis in Anorexia Nervosa: A Population-Based Cohort Study Using the Health Improvement Network.

This population-based retrospective cohort study sought to determine if anorexia nervosa (AN) is associated with a higher risk of urolithiasis. Nine thousand three hundred two females with AN were compared to 92 959 randomly selected age-matched and practice-matched females. Cox regression was used to estimate the hazard ratio (HR) for urolithiasis and evaluate effect modification by age. Twenty-three participants with AN (0.25%) developed urolithiasis compared with 154 unexposed participants (0.17%) over a median of 4 years of observation. The risk of urolithiasis varied significantly with age (interaction p = 0.02). AN was associated with a more than threefold higher risk of urolithiasis in females ≤25 years of age (HR 3.49, 95% CI: 1.56-7.81; p = 0.002), but not in females over 25 years (HR 1.18, 95% CI: 0.69-2.02; p = 0.54). The distribution of diagnosis codes for urolithiasis differed between groups (p = 0.04), with a higher proportion of codes for uric acid urolithiasis in the AN (16.2%) versus unexposed group (5.0%). Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association.

Characterization of Whole Body Pain in Urological Chronic Pelvic Pain Syndrome at Baseline: A MAPP Research Network Study.

PURPOSE: We characterized the location and spatial distribution of whole body pain in patients with urological chronic pelvic pain syndrome using a body map. We also compared the severity of urinary symptoms, pelvic pain, nonpelvic pain and psychosocial health among patients with different pain patterns. MATERIALS AND METHODS: A total of 233 women and 191 men with urological chronic pelvic pain syndrome enrolled in a multicenter, 1-year observational study completed a battery of baseline measures, including a body map describing the location of pain during the last week. Participants were categorized with pelvic pain if they reported pain in the abdomen and pelvis only. Participants who reported pain beyond the pelvis were further divided into 2 subgroups based on the number of broader body regions affected by pain, including an intermediate group with 1 or 2 additional regions outside the pelvis and a widespread pain group with 3 to 7 additional regions. RESULTS: Of the 424 enrolled patients 25% reported pelvic pain only and 75% reported pain beyond the pelvis, of whom 38% reported widespread pain. Participants with a greater number of pain locations had greater nonpelvic pain severity (p <0.0001), sleep disturbance (p = 0.035), depression (p = 0.005), anxiety (p = 0.011), psychological stress (p = 0.005) and negative affect scores (p = 0.0004), and worse quality of life (p ≤0.021). No difference in pelvic pain and urinary symptom severity was observed according to increasing pain distribution. CONCLUSIONS: Three-quarters of the men and women with urological chronic pelvic pain syndrome reported pain outside the pelvis. Widespread pain was associated with greater severity of nonpelvic pain symptoms, poorer psychosocial health and worse quality of life but not with worse pelvic pain or urinary symptoms.

Membrane pressures predict clotting of pediatric continuous renal replacement therapy circuits.

BACKGROUND: Clotting of continuous renal replacement therapy (CRRT) circuits leads to inadequate clearance, decreased ultrafiltration, and increased resource use. We identified factors associated with premature clotting of circuits during CRRT in children. METHODS: In a retrospective cohort of 26 children (median age 11.8 years) receiving 79 CRRT circuits (51 heparin, 22 citrate, 6 using no anticoagulation), we captured hourly pressure, flow, and fluid removal rates along with all activated clotting time (ACT) and circuit ionized calcium measurements. Cox and logistic regression models were used to examine factors associated with premature circuit clotting before the scheduled 3-day circuit change. RESULTS: Of the 79 circuits, 51 (64.6%) underwent unplanned filter change due to filter clotting (median duration 18.25 h, interquartile range [IQR] 9.25, 33.5 h), and 28 (35.4%) underwent scheduled change (median duration 66 h, IQR 61.00, 69.00 h). Patient age, catheter size and location, blood flow rate, and the percentage of pre-filter replacement fluid were not associated with premature clotting. Heparin circuits were less likely than citrate circuits to clot prematurely. Each 1-mmHg increase in the transmembrane or filter pressure was independently associated with a 1.5% (95% confidence interval [CI] 1.0-2.0%) and 1.5% (95% CI 1.0-2.0%) higher risk of clotting, respectively. Higher ACTs were associated with lower transmembrane (p = 0.03) and filter (p < 0.001) pressures. CONCLUSIONS: The majority of circuits in our cohort were subject to unplanned filter changes. Elevated transmembrane and filter pressures were associated with clotting. Our results suggest that maintaining higher ACT may decrease the risk of circuit clotting. Larger studies are needed to examine other factors that may prolong the lifespan of the CRRT circuit in this high-risk population.

Improved power in crossover designs through linear combinations of baselines.

In a crossover design in the absence of any carryover effect, including period-specific baselines as covariates in an analysis of covariance, is known to increase the precision of the estimated treatment effect. The extent of the efficiency gain is a function of the joint covariance structure of the baselines and post-treatment responses, as well as the metric used to incorporate the baselines into the analysis. Here, we show how the underlying covariance structure can be leveraged to find an optimal linear combination of baselines so as to minimize the theoretical variance of the analysis of covariance-based estimated treatment effect. Our work is relevant to complete designs with up to four periods, specifically the 2 × 2, 3 × 3, and 4 × 4. Given that the optimal linear combination of baselines is a function of the covariance structure, which in practice is unknown, we propose an adaptive method. Here, the covariance structure is chosen using information criterion to guide the choice of the linear combination of baselines. Evaluation of the proposed approach suggests that the type I error rate is maintained. Moreover, relative to previously published methods, sizeable gains in power are possible with this method. Results from a 2 × 2 trial exploring renal function, and a 3 × 3 trial with heart rate as the outcome, are used to illustrate the methods. Copyright © 2016 John Wiley & Sons, Ltd.

Symptom Variability and Early Symptom Regression in the MAPP Study: A Prospective Study of Urological Chronic Pelvic Pain Syndrome.

PURPOSE: We examined symptom variability in men and women with urological chronic pelvic pain syndrome. We describe symptom fluctuations as related to early symptom regression and its effect on estimated 1-year symptom change. We also describe a method to quantify patient specific symptom variability. MATERIALS AND METHODS: Symptoms were assessed biweekly in 424 subjects with urological chronic pelvic pain syndrome during 1 year. To evaluate the impact of early symptom regression subjects were classified as improved, no change or worse according to the rate of change using 1) all data, 2) excluding week 0 and 3) excluding weeks 0 and 2. Patient specific, time varying variability was calculated at each interval using a sliding window approach. Patients were classified as high, medium or low variability at each time and ultimately as high or low variability overall based on the variability for the majority of contacts. RESULTS: Prior to excluding early weeks to adjust for early symptom regression 25% to 38% and 5% to 6% of patients were classified as improved and worse, respectively. After adjustment the percent of patients who were improved or worse ranged from 15% to 25% and 6% to 9%, respectively. High and low variability phenotypes were each identified in 25% to 30% of participants. CONCLUSIONS: Patients with urological chronic pelvic pain syndrome show symptom variability. At study enrollment patients had worse symptoms on average, resulting in a regression effect that influenced the estimated proportion of those who were improved or worse. Prospective studies should include a run-in period to account for regression to the mean and other causes of early symptom regression. Further, symptom variability may be quantified and used to characterize longitudinal symptom profiles of urological chronic pelvic pain syndrome.

Fracture Burden and Risk Factors in Childhood CKD: Results from the CKiD Cohort Study.

Childhood chronic kidney disease (CHD) poses multiple threats to bone accrual; however, the associated fracture risk is not well characterized. This prospective cohort study included 537 CKD in Children (CKiD) participants. Fracture histories were obtained at baseline, at years 1, 3, and 5 through November 1, 2009, and annually thereafter. We used Cox regression analysis of first incident fracture to evaluate potential correlates of fracture risk. At enrollment, median age was 11 years, and 16% of patients reported a prior fracture. Over a median of 3.9 years, 43 males and 24 females sustained incident fractures, corresponding to 395 (95% confidence interval [95% CI], 293-533) and 323 (95% CI, 216-481) fractures per 10,000 person-years, respectively. These rates were 2- to 3-fold higher than published general population rates. The only gender difference in fracture risk was a 2.6-fold higher risk in males aged ≥15 years (570/10,000 person-years, adjusted P=0.04). In multivariable analysis, advanced pubertal stage, greater height Z-score, difficulty walking, and higher average log-transformed parathyroid hormone level were independently associated with greater fracture risk (all P≤0.04). Phosphate binder treatment (predominantly calcium-based) was associated with lower fracture risk (hazard ratio, 0.37; 95% CI, 0.15-0.91; P=0.03). Participation in more than one team sport was associated with higher risk (hazard ratio, 4.87; 95% CI, 2.21-10.75; P<0.001). In conclusion, children with CKD have a high burden of fracture. Regarding modifiable factors, higher average parathyroid hormone level was associated with greater risk of fracture, whereas phosphate binder use was protective in this cohort.