What happens to ART-eligible patients who do not start ART? Drop out between screening and ART initiation: a cohort study in Karonga, Malawi

BACKGROUND: Routine ART programme statistics generally only provide information about individuals who start treatment. We aimed to investigate the outcome of those who are eligible but do not start ART in the Malawi programme, factors associated with this dropout, and reasons for not starting treatment, in a prospective cohort study.METHODS: Individuals having a first screening visit at the ART clinic at Karonga District Hospital, northern Malawi, between September 2005 and July 2006 were interviewed. Study follow-up to identify treatment outcomes was conducted at the clinic and in the community. Logistic regression models were used to identify factors associated with dropout before ART initiation among participants identified as clinically eligible for ART.RESULTS: 88 participants eligible for ART at their first screening visit (out of 633, 13.9%) defaulted before starting ART. Participants with less education, difficulties in dressing, a more delayed ART initiation appointment, and mid-upper arm circumference (MUAC) < 22 cm were significantly less likely to have visited the clinic subsequently. Thirty-five (58%) of the 60 participants who defaulted and were tracked at home had died, 21 before their ART initiation appointment.CONCLUSIONS: MUAC and reported difficulties in dressing may provide useful screening indicators to identify sicker ART-eligible individuals at high risk of dropping out of the programme who might benefit from being brought back quickly or admitted to hospital for observation. Individuals with less education may need adapted health information at screening. Deaths of ART-eligible individuals occurring prior to ART initiation are not included in routine programme statistics. Considering all those who are eligible for ART as a denominator for programme indicators would help to highlight this vulnerable group, in order to identify new opportunities for further improving ART programmes

Normal Range of CD4 Cell Counts and Temporal Changes in Two HIVNegative Malawian Populations

Longitudinal studies were carried out to determine trends in CD4 cell counts over a four year period in healthy HIV-negative adults in a rural (134 individuals) and an urban (80 individuals) site in Malawi, using TruCountTM and FACScountTM platforms. At baseline, median counts and 95% ranges were 890 (359-1954) cells per microlitre (μl) and 725 (114-1074) cells/μl respectively. 1.5% and 6% respectively had baseline counts below 350 cells/μl and 1.5% and 2.5% below 250 cells per μl. Transient dips to below 250 cells/μl were observed in seven individuals, with two individuals having persistently low CD4 counts over more than one year. Women and individuals from the urban site were significantly more likely to have “low CD4 count” (< 500 cells/μl) even when adjusted for other factors. In common with neighbouring countries, HIV-negative populations in Malawi have CD4 counts considerably lower than European reference ranges, and healthy individuals may have persistently or transiently low counts. Within Malawi, ranges differ according to the selected population

What happens to ART-eligible patients who do not start ART? Dropout between screening and ART initiation: a cohort study in Karonga, Malawi

BACKGROUND: Routine ART programme statistics generally only provide information about individuals who start treatment. We aimed to investigate the outcome of those who are eligible but do not start ART in the Malawi programme, factors associated with this dropout, and reasons for not starting treatment, in a prospective cohort study. METHODS: Individuals having a first screening visit at the ART clinic at Karonga District Hospital, northern Malawi, between September 2005 and July 2006 were interviewed. Study follow-up to identify treatment outcomes was conducted at the clinic and in the community. Logistic regression models were used to identify factors associated with dropout before ART initiation among participants identified as clinically eligible for ART. RESULTS: 88 participants eligible for ART at their first screening visit (out of 633, 13.9%) defaulted before starting ART. Participants with less education, difficulties in dressing, a more delayed ART initiation appointment, and mid-upper arm circumference (MUAC) < 22 cm were significantly less likely to have visited the clinic subsequently. Thirty-five (58%) of the 60 participants who defaulted and were tracked at home had died, 21 before their ART initiation appointment. CONCLUSIONS: MUAC and reported difficulties in dressing may provide useful screening indicators to identify sicker ART-eligible individuals at high risk of dropping out of the programme who might benefit from being brought back quickly or admitted to hospital for observation. Individuals with less education may need adapted health information at screening. Deaths of ART-eligible individuals occurring prior to ART initiation are not included in routine programme statistics. Considering all those who are eligible for ART as a denominator for programme indicators would help to highlight this vulnerable group, in order to identify new opportunities for further improving ART programmes

HIV-Associated TB in An Giang Province, Vietnam, 2001–2004: Epidemiology and TB Treatment Outcomes

BACKGROUND: Mortality is high in HIV-infected TB patients, but few studies from Southeast Asia have documented the benefits of interventions, such as co-trimoxazole (CTX), in reducing mortality during TB treatment. To help guide policy in Vietnam, we studied the epidemiology of HIV-associated TB in one province and examined factors associated with outcomes, including the impact of CTX use. METHODOLOGY/PRINCIPAL FINDINGS: We retrospectively abstracted data for all HIV-infected persons diagnosed with TB from 2001-2004 in An Giang, a province in southern Vietnam in which TB patients receive HIV counseling and testing. We used standard WHO definitions to classify TB treatment outcomes. We conducted multivariate analysis to identify risk factors for the composite outcome of death, default, or treatment failure during TB treatment. From 2001-2004, 637 HIV-infected TB patients were diagnosed in An Giang. Of these, 501 (79%) were male, 321 (50%) were aged 25-34 years, and the most common self-reported HIV risk factor was sex with a commercial sex worker in 221 (35%). TB was classified as smear-positive in 531 (83%). During TB treatment, 167 (26%) patients died, 9 (1%) defaulted, and 6 (1%) failed treatment. Of 454 patients who took CTX, 116 (26%) had an unsuccessful outcome compared with 33 (70%) of 47 patients who did not take CTX (relative risk, 0.4; 95% confidence interval [CI], 0.3-0.5). Adjusting for male sex, rural residence, TB smear status and disease location, and the occurrence of adverse events during TB treatment in multivariate analysis, the benefit of CTX persisted (adjusted odds ratio for unsuccessful outcome 0.1; CI, 0.1-0.3). CONCLUSIONS/SIGNIFICANCE: In An Giang, Vietnam, HIV-associated TB was associated with poor TB treatment outcomes. Outcomes were significantly better in those taking CTX. This finding suggests that Vietnam should consider applying WHO recommendations to prescribe CTX to all HIV-infected TB patients

Risk Assessment of Pulmonary Metastasis for Cervical Cancer Patients by Ensemble Learning Models: A Large Population Based Real-World Study

Menglin Zhu,1,&ast; Bo Wang,2,&ast; Tiejun Wang,3 Yilin Chen,1,4 Du He1,5 1Department of Anesthesiology, Hubei Minzu University Affiliated Enshi Clinical Medical School, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, 445000, People’s Republic of China; 2National Clinical Research Center for Obstetrical and Gynecological Diseases; Key Laboratory of Cancer Invasion and Metastasis, Ministry of Education; Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 3Department of Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China; 4Department of Pulmonary and Critical Care Medicine, Hubei Minzu University Affiliated Enshi Clinical Medical School, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, 445000, People’s Republic of China; 5Department of Oncology, Hubei Minzu University Affiliated Enshi Clinical Medical School, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, 445000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Du He; Yilin Chen Email [email protected]; [email protected]: Pulmonary metastasis (PM) is an independent risk factor affecting the prognosis of cervical patients, but it still lacks a prediction. This study aimed to develop machine learning-based predictive models for PM.Methods: A total of 22,766 patients diagnosed with or without PM from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in this study. The cohort was randomly split into a train set (70%) and a validation set (30%). In addition, 884 Chinese patients from two tertiary medical centers were included as an external validation set. Duplicated and useless candidate variables were excluded, and sixteen variables were included for the machine learning algorithm. We developed five predictive models, including the generalized linear model (GLM), random forest model (RFM), naive Bayesian model (NBM), artificial neural networks model (ANNM), and decision tree model (DTM). The predictive performance of these models was evaluated by the receiver operating characteristic (ROC) curve and calibration curve. The Cox proportional hazard model (CPHM) and competing risk model (CRM) were also included for survival outcome prediction.Results: Of the patients included in the analysis, 2456 (4.38%) patients were diagnosed with PM. Age, organ-site metastasis (liver, bone, brain), distant lymph metastasis, tumor size, and pathology were the important predictors of PM. The RFM with 9 variables introduced was identified as the best predictive model for PM (AUC = 0.972, 95% CI: 0.958– 0.986). The C-index for the CPHM and CRM was 0.626 (95% CI: 0.604– 0.648) and 0.611 (95% CI: 0.586– 0.636), respectively.Conclusion: The prediction algorithm derived by machine-learning-based methods shows a robust ability to predict PM. This result suggests that machine learning techniques have the potential to improve the development and validation of predictive modeling in cervical patients with PM.Keywords: cervical cancer, pulmonary metastasis, machine learning, predictive model, prognosis, SEER databas

HIV epidemic trend and antiretroviral treatment need in Karonga District, Malawi

We describe the development of the HIV epidemic in Karonga District, Malawi over 22 years using data from population surveys and community samples. These data are used to estimate the trend in HIV prevalence, incidence and need for antiretroviral treatment (ART) using a simple mathematical model. HIV prevalence rose quickly in the late 1980s and early 1990s, stabilizing at around 12% in the mid-1990s. Estimated annual HIV incidence rose quickly, peaking in the early 1990s at 2·2% among males and 3·1% among females, and then levelled off at 1·3% among males and 1·1% among females by the late 1990s. Assuming a 2-year eligibility period, both our model and the UNAIDS models predicted 2·1% of adults were in need of ART in 2005. This prediction was sensitive to the assumed eligibility period, ranging from 1·6% to 2·6% if the eligibility period was instead assumed to be 1·5 or 2·5 years, respectively