Latent class regression improves the predictive acuity and clinical utility of survival prognostication amongst chronic heart failure patients

The present study aimed to compare the predictive acuity of latent class regression (LCR) modelling with: standard generalised linear modelling (GLM); and GLMs that include the membership of subgroups/classes (identified through prior latent class analysis; LCA) as alternative or additional candidate predictors. Using real world demographic and clinical data from 1,802 heart failure patients enrolled in the UK-HEART2 cohort, the study found that univariable GLMs using LCA-generated subgroup/class membership as the sole candidate predictor of survival were inferior to standard multivariable GLMs using the same four covariates as those used in the LCA. The inclusion of the LCA subgroup/class membership together with these four covariates as candidate predictors in a multivariable GLM showed no improvement in predictive acuity. In contrast, LCR modelling resulted in a 18–22% improvement in predictive acuity and provided a range of alternative models from which it would be possible to balance predictive acuity against entropy to select models that were optimally suited to improve the efficient allocation of clinical resources to address the differential risk of the outcome (in this instance, survival). These findings provide proof-of-principle that LCR modelling can improve the predictive acuity of GLMs and enhance the clinical utility of their predictions. These improvements warrant further attention and exploration, including the use of alternative techniques (including machine learning algorithms) that are also capable of generating latent class structure while determining outcome predictions, particularly for use with large and routinely collected clinical datasets, and with binary, count and continuous variables

Statistical and Machine Learning Methods for Risk Prediction in Health

Prediction of occurrence of an event in a patients’ lifecourse is gradually becoming very important in this era of stratified medicine. With the availability of vast amounts of data in the form of Electronic Medical Records (EMRs), many risk prediction models (RPMs) have been developed for use in predicting future events in a patients’ journey. RPMs use joint information collected from multiple predictors to provide a prospective insight into future ‘potential’ outcomes. Recent research developments indicate that there is a keen interest amongst researchers to develop RPMs that can be used to predict future events using routinely available information with optimum accuracy. Improvements in the prediction accuracy of RPMs would provide better quality guidance to health care policy makers in decision making process. Most of RPMs suffer from methodological shortcomings due to the inherent heterogeneity which causes patients to have different underlying risk profiles and therefore respond differently to treatment. Ignoring heterogeneity can affect the performance of RPMs which may lead to bias and poor estimation of the underlying risk for individuals. This thesis explores the benefits of using causal reasoning combined with latent variable methods to systematically improve prediction modelling. Throughout the thesis, the potential benefit of incorporating causal assumptions while predicting health outcomes is introduced through a lifecourse perspective using simulated datasets. Specifically, the thesis examines a latent class Cox proportional hazards (PH) model compared to the standard statistical modelling approaches typically adopted that do not explicitly accommodate population heterogeneity. The thesis also compares the Cox neural network approach which uses machine learning principles against the latent class Cox PH model. Lastly, this thesis explores the idea of predicting change, which is a composite outcome, using simulated datasets representing different possible data-generating scenarios and how this can enhance the RPMs

A comparison of clinical outcomes among people living with HIV of different age groups attending Queen Elizabeth Central Hospital Outpatient ART Clinic in Malawi

Introduction: Adherence to Antiretroviral Treatment (ART) in children and adolescents living with HIV in low-resource settings is not extensively studied in large cohort studies including both adults and pediatric patients. We compared rates of virological suppression, adherence and defaulting among children, adolescents and adults attending a family ART clinic at Queen Elizabeth Central Hospital; a tertiary hospital situated in the southern region of Malawi. Methods: The study was longitudinal and made use of routinely collected data for all 27,229 clinic attendees. Clinical information obtained at routine clinical visits entered electronically since 2008 was extracted in February 2017. This data was used to ascertain differences across the different age groups. Logistic regression and Cox regression models were fitted to compare rates of Virological Suppression (VS), adherence, and defaulting, respectively. Results: Younger and older adolescents (ages 10–14 years and 15–19 years respectively) were less likely to achieve VS compared to adults in the final model AOR 0.4 (0.2–0.9, 95% CI) and AOR 0.2 (0.1–0.4, 95% CI) respectively. Young children (ages 0–4 years), older children (ages 5–9 years) and younger adolescents were less adherent to ART compared to adults AOR 0.1 (0.1–0.2, 95% CI), AOR 0.2 (0.1–0.3, 95% CI), and AOR 0.4 (0.3–0.5, 95% CI) respectively. Young adults and younger children had an increased likelihood of defaulting compared to adults. Conclusion: Poor performance on ART of children and adolescents highlights unaddressed challenges to adherence. Ongoing research to explore these potential barriers and possible interventions needs to be carried out. The adherence assessment methods used and strategies for improving it among children and adolescents need to be revised at the clinic.Publisher PDFPeer reviewe

Early disengagement from HIV pre-exposure prophylaxis services and associated factors among female sex workers in Dar es Salaam, Tanzania: a socioecological approach

Introduction Pre-exposure prophylaxis (PrEP) is an effective HIV prevention tool when taken as prescribed. However, suboptimal use may challenge its real-life impact. To support female sex workers in their efforts to prevent themselves from HIV, it is essential to identify factors that contribute to early disengagement from PrEP care. In this study, we aimed to estimate the risk of early disengagement from PrEP services among female sex workers in Tanzania and associated factors using a socioecological model as a guiding framework.Methods The study was conducted as part of a pragmatic mHealth trial for PrEP roll-out in Dar es Salaam in 2021. We estimated the risk of early disengagement, defined as not presenting for the first follow-up visit (within 56 days of enrolment), and its associations with individual, social, behavioural and structural factors (age, self-perceived HIV risk, mental distress, harmful alcohol use, condom use, number of sex work clients, female sex worker stigma and mobility) using multivariable logistic regression models, with marginal standardisation to obtain adjusted relative risks (aRR).Results Of the 470 female sex workers enrolled in the study, 340 (74.6%) did not attend the first follow-up visit (disengaged). Mental distress (aRR=1.14; 95% CI 1.01 to 1.27) was associated with increased risk of disengagement. Participants who reported a higher number of clients per month (10–29 partners: aRR=0.87; 95% CI 0.76 to 0.98 and ≥30 partners: aRR=0.80; 95% CI 0.68 to 0.91) and older participants (≥35 years) (RR=0.75; 95% CI 0.56 to 0.95) had a lower risk of disengagement.Conclusions and recommendations Early disengagement with the PrEP programme was high. Mental distress, younger age and having fewer clients were risk factors for disengagement. We argue that PrEP programmes could benefit from including mental health screening and treatment, as well as directing attention to younger sex workers and those reporting fewer clients

Pre-pregnancy body mass index (BMI) and maternal gestational weight gain are positively associated with birth outcomes in rural Malawi.

BACKGROUND:Whereas poor maternal nutritional status before and during pregnancy is widely associated with adverse birth outcomes, studies quantifying this association in low income countries are scarce. We examined whether maternal pre-pregnancy body mass index (BMI) and weight gain during pregnancy are associated with birth outcomes in rural Malawi. METHODS:We analyzed the associations between pre-pregnancy BMI and average weekly gestational weight gain (WWG) and birth outcomes [duration of gestation, birth weight, length-for-age z-score (LAZ), and head circumference-for-age z-score (HCZ)]. We also determined whether women with low or high pre-pregnancy BMI or women with inadequate or excessive WWG were at increased risk of adverse birth outcomes. RESULTS:The analyses included 1287 women with a mean BMI of 21.8 kg/m2, of whom 5.9% were underweight (< 18.5 kg/m2), 10.9% were overweight (≥ 25 kg/m2), 71.8% had low WWG [below the lower limit of the Institute of Medicine (IOM) recommendation], and 5.2% had high WWG (above IOM recommendation). In adjusted models, pre-pregnancy BMI was not associated with duration of pregnancy (p = 0.926), but was positively associated with birth weight and HCZ (<0.001 and p = 0.003, respectively). WWG was positively associated with duration of gestation (p = 0.031), birth weight (p<0.001), LAZ (p<0.001), and HCZ (p<0.001). Compared to normal weight women, underweight women were at increased risk of having stunted infants (p = 0.029). Women with low WWG were at increased risk of having infants with low birth weight (p = 0.006) and small head circumference (p = 0.024) compared to those with normal weight gain. Those with high BMI or high WWG were not at increased risk of adverse birth outcomes. CONCLUSIONS:WWG is an important predictor of birth outcomes in rural Malawi. The high prevalence of inadequate WWG compared to low pre-pregnancy BMI highlights the need to investigate causes of inadequate weight gain in this region

The association of malaria morbidity with linear growth, hemoglobin, iron status, and development in young Malawian children: a prospective cohort study.

BackgroundAlthough poor complementary feeding is associated with poor child growth, nutrition interventions only have modest impact on child growth, due to high burden of infections. We aimed to assess the association of malaria with linear growth, hemoglobin, iron status, and development in children aged 6-18 months in a setting of high malaria and undernutrition prevalence.MethodsProspective cohort study, conducted in Mangochi district, Malawi. We enrolled six-months-old infants and collected weekly data for 'presumed' malaria, diarrhea, and acute respiratory infections (ARI) until age 18 months. Change in length-for-age z-scores (LAZ), stunting, hemoglobin, iron status, and development were assessed at age 18 months. We used ordinary least squares regression for continuous outcomes and modified Poisson regression for categorical outcomes.ResultsOf the 2723 children enrolled, 2016 (74.0%) had complete measurements. The mean (standard deviation) incidences of 'presumed' malaria, diarrhea, and ARI, respectively were: 1.4 (2.0), 4.6 (10.1), and 8.3 (5.0) episodes/child year. Prevalence of stunting increased from 27.4 to 41.5% from 6 to 18 months. 'Presumed' malaria incidence was associated with higher risk of stunting (risk ratio [RR] = 1.04, 95% confidence interval [CI] = 1.01 to 1.07, p = 0.023), anemia (RR = 1.02, 95%CI = 1.00 to 1.04, p = 0.014) and better socio-emotional scores (B = - 0.21, 95%CI = - 0.39 to - 0.03, p = 0.041), but not with change in LAZ, haemoglobin, iron status or other developmental outcomes. Diarrhea incidence was associated with change in LAZ (B = - 0.02; 95% CI = - 0.03 to - 0.01; p = 0.009), stunting (RR = 1.02; 95% CI = 1.01 to 1.03; p = 0.005), and slower motor development. ARI incidence was not associated with any outcome except for poorer socio-emotional scores.ConclusionIn this population of young children living in a malaria-endemic setting, with active surveillance and treatment, 'presumed' malaria is not associated with change in LAZ, hemoglobin, or iron status, but could be associated with stunting and anemia. Diarrhea was more consistently associated with growth than was malaria or ARI. The findings may be different in contexts where active malaria surveillance and treatment is not provided.Trial registrationNCT00945698 (July 24, 2009) and NCT01239693 (November 11, 2010)

Providing lipid-based nutrient supplement during pregnancy does not reduce the risk of maternal P falciparum parasitaemia and reproductive tract infections: a randomised controlled trial.

BackgroundMaternal infections are associated with maternal and foetal adverse outcomes. Nutrient supplementation during pregnancy may reduce the occurrence of infections by improving maternal immunity. We aimed to investigate the impact of small-quantity lipid-based nutrient supplement (SQ-LNS) on the occurrence of Plasmodium falciparum parasitaemia during pregnancy and trichomoniasis, vaginal candidiasis and urinary tract infection (UTI) after delivery.MethodsPregnant Malawian women enrolled in the iLiNS-DYAD trial receiving daily supplementation with SQ-LNS, multiple micronutrients (MMN) or iron &amp; folic acid (IFA) from &lt;20 gestation weeks (gw) were assessed for P. falciparum parasitaemia at 32 gw using rapid diagnostic testing (RDT), at 36 gw using polymerase chain reaction (PCR) and at delivery using both RDT and PCR; and at one week after delivery for trichomoniasis and vaginal candidiasis using wet mount microscopy and for UTI using urine dipstick analysis. The prevalence of each infection by intervention group was estimated at the prescribed time points and the global null hypothesis was tested using logistic regression. Adjusted analyses were performed using preselected covariates.ResultsThe prevalence of P. falciparum parasitaemia was 10.7% at 32 gw, 9% at 36 gw, and 8.3% by RDT and 20.2% by PCR at delivery. After delivery the prevalence of trichomoniasis was 10.5%, vaginal candidiasis was 0.5%, and UTI was 3.1%. There were no differences between intervention groups in the prevalence of any of the infections.ConclusionIn this population, SQ-LNS did not influence the occurrence of maternal P. falciparum parasitaemia, trichomoniasis, vaginal candidiasis or UTI.Trial registrationIdentifier: NCT01239693 (10 November 2010)