Predicting Outcome on Admission and Post-Admission for Acetaminophen-Induced Acute Liver Failure Using Classification and Regression Tree Models

Background/Aim

Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients often presents significant challenges. King’s College (KCC) has been validated on hospital admission, but little has been published on later phases of illness. We aimed to improve determinations of prognosis both at the time of and following admission for APAP-ALF using Classification and Regression Tree (CART) models.

Methods

CART models were applied to US ALFSG registry data to predict 21-day death or liver transplant early (on admission) and post-admission (days 3-7) for 803 APAP-ALF patients enrolled 01/1998–09/2013. Accuracy in prediction of outcome (AC), sensitivity (SN), specificity (SP), and area under receiver-operating curve (AUROC) were compared between 3 models: KCC (INR, creatinine, coma grade, pH), CART analysis using only KCC variables (KCC-CART) and a CART model using new variables (NEW-CART).

Results

Traditional KCC yielded 69% AC, 90% SP, 27% SN, and 0.58 AUROC on admission, with similar performance post-admission. KCC-CART at admission offered predictive 66% AC, 65% SP, 67% SN, and 0.74 AUROC. Post-admission, KCC-CART had predictive 82% AC, 86% SP, 46% SN and 0.81 AUROC. NEW-CART models using MELD (Model for end stage liver disease), lactate and mechanical ventilation on admission yielded predictive 72% AC, 71% SP, 77% SN and AUROC 0.79. For later stages, NEW-CART (MELD, lactate, coma grade) offered predictive AC 86%, SP 91%, SN 46%, AUROC 0.73.

Conclusion

CARTs offer simple prognostic models for APAP-ALF patients, which have higher AUROC and SN than KCC, with similar AC and negligibly worse SP. Admission and post-admission predictions were developed.

Key Points

• Prognostication in acetaminophen-induced acute liver failure (APAP-ALF) is challenging beyond admission• Little has been published regarding the use of King’s College Criteria (KCC) beyond admission and KCC has shown limited sensitivity in subsequent studies• Classification and Regression Tree (CART) methodology allows the development of predictive models using binary splits and offers an intuitive method for predicting outcome, using processes familiar to clinicians• Data from the ALFSG registry suggested that CART prognosis models for the APAP population offer improved sensitivity and model performance over traditional regression-based KCC, while maintaining similar accuracy and negligibly worse specificity• KCC-CART models offered modest improvement over traditional KCC, with NEW-CART models performing better than KCC-CART particularly at late time points     

Methods for Specifying the Target Difference in a Randomised Controlled Trial: The Difference ELicitation in TriAls (DELTA) Systematic Review

Background

Randomised controlled trials (RCTs) are widely accepted as the preferred study design for evaluating healthcare interventions. When the sample size is determined, a (target) difference is typically specified that the RCT is designed to detect. This provides reassurance that the study will be informative, i.e., should such a difference exist, it is likely to be detected with the required statistical precision. The aim of this review was to identify potential methods for specifying the target difference in an RCT sample size calculation.

Methods and Findings

A comprehensive systematic review of medical and non-medical literature was carried out for methods that could be used to specify the target difference for an RCT sample size calculation. The databases searched were MEDLINE, MEDLINE In-Process, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, the Education Resources Information Center (ERIC), and Scopus (for in-press publications); the search period was from 1966 or the earliest date covered, to between November 2010 and January 2011. Additionally, textbooks addressing the methodology of clinical trials and International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) tripartite guidelines for clinical trials were also consulted. A narrative synthesis of methods was produced. Studies that described a method that could be used for specifying an important and/or realistic difference were included. The search identified 11,485 potentially relevant articles from the databases searched. Of these, 1,434 were selected for full-text assessment, and a further nine were identified from other sources. Fifteen clinical trial textbooks and the ICH tripartite guidelines were also reviewed. In total, 777 studies were included, and within them, seven methods were identified—anchor, distribution, health economic, opinion-seeking, pilot study, review of the evidence base, and standardised effect size.

Conclusions

A variety of methods are available that researchers can use for specifying the target difference in an RCT sample size calculation. Appropriate methods may vary depending on the aim (e.g., specifying an important difference versus a realistic difference), context (e.g., research question and availability of data), and underlying framework adopted (e.g., Bayesian versus conventional statistical approach). Guidance on the use of each method is given. No single method provides a perfect solution for all contexts. Please see later in the article for the Editors'' Summary     

A Risk Prediction Model for the Assessment and Triage of Women with Hypertensive Disorders of Pregnancy in Low-Resourced Settings: The miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) Multi-country Prospective Cohort Study

Background

Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications.

Methods and Findings

From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735–0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658–0.768). A predicted probability ≥25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability.

Conclusions

The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care. Please see later in the article for the Editors'' Summary     

Risk Stratification by Self-Measured Home Blood Pressure across Categories of Conventional Blood Pressure: A Participant-Level Meta-Analysis

Background

The Global Burden of Diseases Study 2010 reported that hypertension is worldwide the leading risk factor for cardiovascular disease, causing 9.4 million deaths annually. We examined to what extent self-measurement of home blood pressure (HBP) refines risk stratification across increasing categories of conventional blood pressure (CBP).

Methods and Findings

This meta-analysis included 5,008 individuals randomly recruited from five populations (56.6% women; mean age, 57.1 y). All were not treated with antihypertensive drugs. In multivariable analyses, hazard ratios (HRs) associated with 10-mm Hg increases in systolic HBP were computed across CBP categories, using the following systolic/diastolic CBP thresholds (in mm Hg): optimal, <120/<80; normal, 120–129/80–84; high-normal, 130–139/85–89; mild hypertension, 140–159/90–99; and severe hypertension, ≥160/≥100.Over 8.3 y, 522 participants died, and 414, 225, and 194 had cardiovascular, cardiac, and cerebrovascular events, respectively. In participants with optimal or normal CBP, HRs for a composite cardiovascular end point associated with a 10-mm Hg higher systolic HBP were 1.28 (1.01–1.62) and 1.22 (1.00–1.49), respectively. At high-normal CBP and in mild hypertension, the HRs were 1.24 (1.03–1.49) and 1.20 (1.06–1.37), respectively, for all cardiovascular events and 1.33 (1.07–1.65) and 1.30 (1.09–1.56), respectively, for stroke. In severe hypertension, the HRs were not significant (p≥0.20). Among people with optimal, normal, and high-normal CBP, 67 (5.0%), 187 (18.4%), and 315 (30.3%), respectively, had masked hypertension (HBP≥130 mm Hg systolic or ≥85 mm Hg diastolic). Compared to true optimal CBP, masked hypertension was associated with a 2.3-fold (1.5–3.5) higher cardiovascular risk. A limitation was few data from low- and middle-income countries.

Conclusions

HBP substantially refines risk stratification at CBP levels assumed to carry no or only mildly increased risk, in particular in the presence of masked hypertension. Randomized trials could help determine the best use of CBP vs. HBP in guiding BP management. Our study identified a novel indication for HBP, which, in view of its low cost and the increased availability of electronic communication, might be globally applicable, even in remote areas or in low-resource settings. Please see later in the article for the Editors'' Summary     

Fetal Growth and Risk of Stillbirth: A Population-Based Case–Control Study

Background

Stillbirth is strongly related to impaired fetal growth. However, the relationship between fetal growth and stillbirth is difficult to determine because of uncertainty in the timing of death and confounding characteristics affecting normal fetal growth.

Methods and Findings

We conducted a population-based case–control study of all stillbirths and a representative sample of live births in 59 hospitals in five geographic areas in the US. Fetal growth abnormalities were categorized as small for gestational age (SGA) (<10th percentile) or large for gestational age (LGA) (>90th percentile) at death (stillbirth) or delivery (live birth) using population, ultrasound, and individualized norms. Gestational age at death was determined using an algorithm that considered the time-of-death interval, postmortem examination, and reliability of the gestational age estimate. Data were weighted to account for the sampling design and differential participation rates in various subgroups. Among 527 singleton stillbirths and 1,821 singleton live births studied, stillbirth was associated with SGA based on population, ultrasound, and individualized norms (odds ratio [OR] [95% CI]: 3.0 [2.2 to 4.0]; 4.7 [3.7 to 5.9]; 4.6 [3.6 to 5.9], respectively). LGA was also associated with increased risk of stillbirth using ultrasound and individualized norms (OR [95% CI]: 3.5 [2.4 to 5.0]; 2.3 [1.7 to 3.1], respectively), but not population norms (OR [95% CI]: 0.6 [0.4 to 1.0]). The associations were stronger with more severe SGA and LGA (<5th and >95th percentile). Analyses adjusted for stillbirth risk factors, subset analyses excluding potential confounders, and analyses in preterm and term pregnancies showed similar patterns of association. In this study 70% of cases and 63% of controls agreed to participate. Analysis weights accounted for differences between consenting and non-consenting women. Some of the characteristics used for individualized fetal growth estimates were missing and were replaced with reference values. However, a sensitivity analysis using individualized norms based on the subset of stillbirths and live births with non-missing variables showed similar findings.

Conclusions

Stillbirth is associated with both growth restriction and excessive fetal growth. These findings suggest that, contrary to current practices and recommendations, stillbirth prevention strategies should focus on both severe SGA and severe LGA pregnancies. Please see later in the article for the Editors'' Summary     

Red Blood Cell Transfusion and Mortality in Trauma Patients: Risk-Stratified Analysis of an Observational Study

Background

Haemorrhage is a common cause of death in trauma patients. Although transfusions are extensively used in the care of bleeding trauma patients, there is uncertainty about the balance of risks and benefits and how this balance depends on the baseline risk of death. Our objective was to evaluate the association of red blood cell (RBC) transfusion with mortality according to the predicted risk of death.

Methods and Findings

A secondary analysis of the CRASH-2 trial (which originally evaluated the effect of tranexamic acid on mortality in trauma patients) was conducted. The trial included 20,127 trauma patients with significant bleeding from 274 hospitals in 40 countries. We evaluated the association of RBC transfusion with mortality in four strata of predicted risk of death: <6%, 6%–20%, 21%–50%, and >50%. For this analysis the exposure considered was RBC transfusion, and the main outcome was death from all causes at 28 days. A total of 10,227 patients (50.8%) received at least one transfusion. We found strong evidence that the association of transfusion with all-cause mortality varied according to the predicted risk of death (p-value for interaction <0.0001). Transfusion was associated with an increase in all-cause mortality among patients with <6% and 6%–20% predicted risk of death (odds ratio [OR] 5.40, 95% CI 4.08–7.13, p<0.0001, and OR 2.31, 95% CI 1.96–2.73, p<0.0001, respectively), but with a decrease in all-cause mortality in patients with >50% predicted risk of death (OR 0.59, 95% CI 0.47–0.74, p<0.0001). Transfusion was associated with an increase in fatal and non-fatal vascular events (OR 2.58, 95% CI 2.05–3.24, p<0.0001). The risk associated with RBC transfusion was significantly increased for all the predicted risk of death categories, but the relative increase was higher for those with the lowest (<6%) predicted risk of death (p-value for interaction <0.0001). As this was an observational study, the results could have been affected by different types of confounding. In addition, we could not consider haemoglobin in our analysis. In sensitivity analyses, excluding patients who died early; conducting propensity score analysis adjusting by use of platelets, fresh frozen plasma, and cryoprecipitate; and adjusting for country produced results that were similar.

Conclusions

The association of transfusion with all-cause mortality appears to vary according to the predicted risk of death. Transfusion may reduce mortality in patients at high risk of death but increase mortality in those at low risk. The effect of transfusion in low-risk patients should be further tested in a randomised trial.

Trial registration

www.ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01746953","term_id":"NCT01746953"}}NCT01746953 Please see later in the article for the Editors'' Summary     

HIV-1 RNA Levels and Antiretroviral Drug Resistance in Blood and Non-Blood Compartments from HIV-1–Infected Men and Women enrolled in AIDS Clinical Trials Group Study A5077

Background

Detectable HIV-1 in body compartments can lead to transmission and antiretroviral resistance. Although sex differences in viral shedding have been demonstrated, mechanisms and magnitude are unclear. We compared RNA levels in blood, genital-secretions and saliva; and drug resistance in plasma and genital-secretions of men and women starting/changing antiretroviral therapy (ART) in the AIDS Clinical Trials Group (ACTG) 5077 study.

Methods

Blood, saliva and genital-secretions (compartment fluids) were collected from HIV-infected adults (≥13 years) at 14 United-States sites, who were initiating or changing ART with plasma viral load (VL) ≥2,000 copies/mL. VL testing was performed on all compartment fluids and HIV resistance genotyping on plasma and genital-secretions. Spearman rank correlations were used to evaluate concordance and Fisher’s and McNemar’s exact tests to compare VL between sexes and among compartments.

Results

Samples were available for 143 subjects; 36% treated (23 men, 29 women) and 64% ‘untreated’ (40 men, 51 women). RNA detection was significantly more frequent in plasma (100%) than genital-secretions (57%) and saliva (64%) (P<0.001). A higher proportion of men had genital shedding versus women (78% versus 41%), and RNA detection was more frequent in saliva versus genital-secretions in women when adjusted for censoring at the limit of assay detection. Inter-compartment fluid VL concordance was low in both sexes. In 22 (13 men, 9 women) paired plasma-genital-secretion genotypes from treated subjects, most had detectable resistance in both plasma (77%) and genital-secretions (68%). Resistance discordance was observed between compartments in 14% of subjects.

Conclusions

HIV shedding and drug resistance detection prior to initiation/change of ART in ACTG 5077 subjects differed among tissues and between sexes, making the gold standard blood-plasma compartment assessment not fully representative of HIV at other tissue sites. Mechanisms of potential sex-dependent tissue compartmentalization should be further characterized to aid in optimizing treatment and prevention of HIV transmission.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00007488","term_id":"NCT00007488"}}NCT00007488     

Atorvastatin Added to Interferon Beta for Relapsing Multiple Sclerosis: 12-Month Treatment Extension of the Randomized Multicenter SWABIMS Trial

Background

Statins have anti-inflammatory and immunomodulatory properties in addition to lipid-lowering effects.

Objectives

To report the 12-month extension of a phase II trial evaluating the efficacy, safety and tolerability of atorvastatin 40 mg/d added to interferon beta-1b (IFNB-1b) in relapsing-remitting multiple sclerosis (RRMS).

Methods

In the randomized, multicenter, parallel-group, rater-blinded core study, 77 RRMS patients started IFNB-1b. At month three they were randomized 1∶1 to receive atorvastatin 40 mg/d or not in addition to IFNB-1b until month 15. In the subsequent extension study, patients continued with unchanged medication for another 12 months. Data at study end were compared to data at month three of the core study.

Results

27 of 72 patients that finished the core study entered the extension study. 45 patients were lost mainly due to a safety analysis during the core study including a recruitment stop for the extension study. The primary end point, the proportion of patients with new lesions on T2-weighted images was equal in both groups (odds ratio 1.926; 95% CI 0.265–14.0007; p = 0.51). All secondary endpoints including number of new lesions and total lesion volume on T2-weighted images, total number of Gd-enhancing lesions on T1-weighted images, volume of grey and white matter, EDSS, MSFC, relapse rate, number of relapse-free patients and neutralizing antibodies did not show significant differences either. The combination therapy was well tolerated.

Conclusions

Atorvastatin 40 mg/day in addition to IFNB-1b did not have any beneficial effects on RRMS compared to IFNB-1b monotherapy over a period of 24 months.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01111656","term_id":"NCT01111656"}}NCT01111656     

AIF Downregulation and Its Interaction with STK3 in Renal Cell Carcinoma

Apoptosis-inducing factor (AIF) plays a crucial role in caspase-independent programmed cell death by triggering chromatin condensation and DNA fragmentation. Therefore, it might be involved in cell homeostasis and tumor development. In this study, we report significant AIF downregulation in the majority of renal cell carcinomas (RCC). In a group of RCC specimens, 84% (43 out of 51) had AIF downregulation by immunohistochemistry stain. Additional 10 kidney tumors, including an oxyphilic adenoma, also had significant AIF downregulation by Northern blot analysis. The mechanisms of the AIF downregulation included both AIF deletion and its promoter methylation. Forced expression of AIF in RCC cell lines induced massive apoptosis. Further analysis revealed that AIF interacted with STK3, a known regulator of apoptosis, and enhanced its phosphorylation at Thr180. These results suggest that AIF downregulation is a common event in kidney tumor development. AIF loss may lead to decreased STK3 activity, defective apoptosis and malignant transformation.     

Longitudinal Analysis Is More Powerful than Cross-Sectional Analysis in Detecting Genetic Association with Neuroimaging Phenotypes

Most existing genome-wide association analyses are cross-sectional, utilizing only phenotypic data at a single time point, e.g. baseline. On the other hand, longitudinal studies, such as Alzheimer''s Disease Neuroimaging Initiative (ADNI), collect phenotypic information at multiple time points. In this article, as a case study, we conducted both longitudinal and cross-sectional analyses of the ADNI data with several brain imaging (not clinical diagnosis) phenotypes, demonstrating the power gains of longitudinal analysis over cross-sectional analysis. Specifically, we scanned genome-wide single nucleotide polymorphisms (SNPs) with 56 brain-wide imaging phenotypes processed by FreeSurfer on 638 subjects. At the genome-wide significance level () or a less stringent level (e.g. ), longitudinal analysis of the phenotypic data from the baseline to month 48 identified more SNP-phenotype associations than cross-sectional analysis of only the baseline data. In particular, at the genome-wide significance level, both SNP rs429358 in gene APOE and SNP rs2075650 in gene TOMM40 were confirmed to be associated with various imaging phenotypes in multiple regions of interests (ROIs) by both analyses, though longitudinal analysis detected more regional phenotypes associated with the two SNPs and indicated another significant SNP rs439401 in gene APOE. In light of the power advantage of longitudinal analysis, we advocate its use in current and future longitudinal neuroimaging studies.