Association between longitudinal biomarkers and major adverse liver outcomes in patients with non-cirrhotic metabolic dysfunction-associated steatotic liver disease.

BACKGROUND AND AIMS: Noninvasive biomarkers provide prognostic information for the development of major adverse liver outcomes (MALOs) in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), but the predictive value of longitudinal biomarker measurements has not been evaluated. We assessed whether changes in biomarkers could predict incident MALO in MASLD. APPROACH AND RESULTS: We analyzed a cohort of 1260 patients (71.7% on biopsy) with non-cirrhotic MASLD between 1974 and 2019. Data at baseline and follow-up visits were obtained from medical charts. MALO was determined through medical charts and linkage to national registers until the end of 2020. A joint modeling approach was used to quantify the associations between the trajectory of biomarkers and the risk of MALO. MASLD was diagnosed at a median age of 52 years (IQR: 39-60), and 59% were male. During a median follow-up of 12.2 years, 111 (8.8%) patients developed MALO. The joint modeling showed that an elevated fibrosis-4 score (HR: 2.60, 95% CI: 1.89-3.50), aspartate aminotransferase (HR: 2.69, 95% CI: 2.57-3.05), and lower platelet count (HR: 0.93, 95% CI: 0.90-0.97) at any time point were associated with an increased risk of MALO, whereas the rate of change in these biomarkers had no association with this risk. CONCLUSIONS: In addition to baseline measurements of noninvasive biomarkers such as fibrosis-4 score, aspartate aminotransferase, and platelets taken at MASLD diagnosis, monitoring their values over time is important, as the latest value of these biomarkers is closely associated with the risk of future MALO. The rate of change may not be as important.

Exploratory subgroup identification in the heterogeneous Cox model: A relatively simple procedure.

For survival analysis applications we propose a novel procedure for identifying subgroups with large treatment effects, with focus on subgroups where treatment is potentially detrimental. The approach, termed forest search, is relatively simple and flexible. All-possible subgroups are screened and selected based on hazard ratio thresholds indicative of harm with assessment according to the standard Cox model. By reversing the role of treatment one can seek to identify substantial benefit. We apply a splitting consistency criteria to identify a subgroup considered "maximally consistent with harm." The type-1 error and power for subgroup identification can be quickly approximated by numerical integration. To aid inference we describe a bootstrap bias-corrected Cox model estimator with variance estimated by a Jacknife approximation. We provide a detailed evaluation of operating characteristics in simulations and compare to virtual twins and generalized random forests where we find the proposal to have favorable performance. In particular, in our simulation setting, we find the proposed approach favorably controls the type-1 error for falsely identifying heterogeneity with higher power and classification accuracy for substantial heterogeneous effects. Two real data applications are provided for publicly available datasets from a clinical trial in oncology, and HIV.

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.

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.

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.

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.

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.

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.