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

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

Assessing Tuberculosis Case Fatality Ratio: A Meta-Analysis

Background: Recently, the tuberculosis (TB) Task Force Impact Measurement acknowledged the need to review the assumptions underlying the TB mortality estimates published annually by the World Health Organization (WHO). TB mortality is indirectly measured by multiplying estimated TB incidence with estimated case fatality ratio (CFR). We conducted a meta-analysis to estimate the TB case fatality ratio in TB patients having initiated TB treatment. Methods: We searched for eligible studies in the PubMed and Embase databases through March 4(th) 2011 and by reference listing of relevant review articles. Main analyses included the estimation of the pooled percentages of: a) TB patients dying due to TB after having initiated TB treatment and b) TB patients dying during TB treatment. Pooled percentages were estimated using random effects regression models on the combined patient population from all studies. Main Results: We identified 69 relevant studies of which 22 provided data on mortality due to TB and 59 provided data on mortality during TB treatment. Among HIV infected persons the pooled percentage of TB patients dying due to TB was 9.2% (95% Confidence Interval (CI): 3.7%-14.7%) and among HIV uninfected persons 3.0% (95% CI: 21.2%-7.4%) based on the results of eight and three studies respectively providing data for this analyses. The pooled percentage of TB patients dying during TB treatment was 18.8% (95% CI: 14.8%-22.8%) among HIV infected patients and 3.5% (95% CI: 2.0%-4.92%) among HIV uninfected patients based on the results of 27 and 19 studies respectively. Conclusion: The results of the literature review are useful in generating prior distributions of CFR in countries with vital registration systems and have contributed towards revised estimates of TB mortality This literature review did not provide us with all data needed for a valid estimation of TB CFR in TB patients initiating TB treatmen

DNA fingerprint changes in tuberculosis: reinfection, evolution, or laboratory error?

BACKGROUND: DNA fingerprint patterns of Mycobacterium tuberculosis strains vary within individuals and between epidemiologically linked individuals because of pattern evolution, new infections, and laboratory error. We explored the importance of these factors. METHODS: Cultures from individuals in northern Malawi who had been diagnosed with tuberculosis (TB) during 1996-2001 were fingerprinted with restriction fragment-length polymorphism (RFLP). Probable laboratory error was inferred by use of dates or isolated positive cultures. Pattern evolution was explored within and between individuals, and the relative importance of relapse and reinfection was estimated in individuals with recurrent TB. RESULTS: RFLP results were available for 930 isolates from 806 individuals. The maximum laboratory-error rate was 3.9%. Pattern evolution was more common in linked individuals (17%) than on relapse (11%) or during treatment (3%). Twenty individuals had recurrent TB after completing treatment: in human immunodeficiency virus (HIV)-positive individuals, 7 of 12 recurrences were due to reinfection, compared with 0 of 8 in HIV-negative individuals (P=.01). CONCLUSIONS: The rate of DNA fingerprint-pattern evolution is not linear, and rates of change calculated from repeat cultures within individuals may not be applicable to transmission between individuals. The high proportion of recurrence due to reinfection found in HIV-positive individuals suggests that secondary prophylaxis and/or antiretroviral treatments are needed for such individuals

Comparison of two versus three smears in identifying culture-positive tuberculosis patients in a rural African setting with high HIV prevalence.

SETTING: Karonga district, northern Malawi. OBJECTIVE: To compare the sensitivity and specificity of two versus three smears for the diagnosis of pulmonary tuberculosis in a setting with high HIV prevalence. DESIGN: A total of 1992 pulmonary tuberculosis suspects with three sputum smears taken over a 2-7 day period and at least one culture result were studied. Smears were auramine stained and examined using fluorescence microscopy, and positives were confirmed with Ziehl-Neelsen staining and light microscopy. Cultures were set up on Löwenstein-Jensen media. True negative and positive status was defined on the basis of culture. The sensitivity, specificity, and positive and negative predictive values of two and three smears were compared. RESULTS: Compared to culture, the sensitivity, specificity, and positive and negative predictive values of three smears were 70%, 98%, 92%, and 92%, respectively. Restriction to the first two smears gave similar results. Of those detected as smear-positive using three smears, at least 97% would have been detected by two. Among those with HIV serology results available, the sensitivity of two smears for detecting culture-positive tuberculosis was identical to that using three. CONCLUSION: In this setting, using fluorescence and light microscopy, collecting two smears rather than three would only marginally reduce sensitivity and would slightly improve the specificity of diagnosis of tuberculosis; this is unaffected by HIV status. The potential for improving specificity is important because of the costs of misdiagnosis. In practice, both sensitivity and specificity may be increased due to the time saved by examining two rather than three smears

Implementation issues in tuberculosis/HIV program collaboration and integration: 3 case studies.

The many interactions between tuberculosis (TB) and human immunodeficiency virus (HIV) infection influence the design and implementation of programs to address the needs of patients living with or at risk for both diseases. Collaboration between national TB and HIV programs and some degree of integration of services at a local level have been advocated by the World Health Organization and other international bodies and are recognized as essential in areas where the 2 diseases are prevalent. However, in most settings, strategies to accomplish this are only beginning to reach the field where their impact will be made and the expectation of improving the outcome of both diseases realized. In this article, 3 such strategies, offering varying degrees of collaboration and integration, are described, 1 at a national level in Malawi and 2 at local sites in South Africa. These geographically and programmatically distinct experiences in TB/HIV service integration are instructive, illustrate common themes, and show that the strategy can be successful, but they also show that programmatic, medical, staffing, resource, and scale-up challenges remain. In addition, they indicate that, although broad program principles of TB/HIV service integration are essential, program designs and components may vary by country and even within countries, as a result of differing TB and HIV disease prevalences, resources, levels of expertise, and differences in program settings (urban vs. rural and/or primary vs. district vs. specialty site). Large national programs can successfully provide rapid, uniform and widespread change and implementation but also must negotiate the subtleties of intricacies of TB/HIV interactions, which confound a uniform "one size fits all" public health approach. Conversely, smaller demonstration projects, even with successful outcomes, must grapple with issues related to generalization of findings, wider implementation, and scale up, to benefit larger populations of those in need

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

Menglin Zhu,1,* Bo Wang,2,* 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*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