Sampling-Based Approaches to Improve Estimation of Mortality among Patient Dropouts: Experience from a Large PEPFAR-Funded Program in Western Kenya (original) (raw)
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Clinical Infectious Diseases, 2006
The scale-up of antiretroviral treatment (ART) services in resource-limited settings requires a programmatic model to deliver care to large numbers of people. Understanding the determinants of key outcome measures--including death and nondeath losses--would assist in program evaluation and development. Between September 2002 and August 2005, all in-program (pretreatment and on-treatment) deaths and nondeath losses were prospectively ascertained among treatment-naive adults (n=1235) who were enrolled in a community-based ART program in South Africa. At study censorship, 927 patients had initiated ART after a median of 34 days after enrollment in the program. One hundred twenty-one (9.8%) patients died. Mortality rates were 33.3 (95% CI, 25.5-43.0), 19.1 (95% CI, 14.4-25.2), and 2.9 (95% CI, 1.8-4.8) deaths/100 person-years in the pretreatment interval, during the first 4 months of ART (early deaths), and after 4 months of ART (late deaths), respectively. Pretreatment and early treatment deaths together accounted for 87% of deaths, and were independently associated with advanced immunodeficiency at enrollment. Late deaths were comparatively few and were only associated with the response to ART at 4 months. Nondeath program losses (loss to follow-up, 2.3%; transfer-out, 1.9%; relocation, 0.7%) were not associated with immune status and were evenly distributed during the study period. Loss to follow-up and late mortality rates were low, reflecting good cohort retention and treatment response. However, the extremely high pretreatment and early mortality rates indicate that patients are enrolling in ART programs with far too advanced immunodeficiency. Causes of late access to the ART program, such as delays in health care access, health system delays, or inappropriate treatment criteria, need to be addressed.
Tropical Medicine & International Health, 2010
Objective To date, data regarding the determinants of mortality in HIV-infected patients starting antiretroviral therapy (ART) in Africa have been primarily derived from routine clinical care settings practicing the public health approach. Losses to follow-up, however, are high in these settings and may lead to bias in understanding the determinants of mortality.Methods We evaluated HIV-infected adults initiating ART between January 1, 2004 and September 30th, 2007 in an ART clinic in southwestern Uganda. Clinical and demographic characteristics were obtained through routine clinical care. In evaluating determinants of mortality, a ‘naïve’ analysis used only deaths known through routine processes. A ‘sample-corrected’ approach incorporated, through probability weights, outcomes from a representative sample of patients lost to follow-up whose vital status was ascertained through tracking in the community.Results In 3,628 patients followed for up to 3.75 years after ART initiation, the ‘naïve’ approach identified male sex and lower pre-ART CD4 count as independent determinants of mortality. The ‘sample-corrected’ approach found lower pre-ART CD4 count, older age, lower weight and calendar year of ART initiation, but not male sex, to be independent determinants of mortality.Conclusions Analyses to identify determinants of mortality in HIV-infected patients on ART in Africa that do not account for losses to follow-up can identify spurious associations and miss actual relationships – both with the potential to mislead public health efforts. A sampling-based approach to account for losses to follow-up represents a feasible and potentially scalable method to strengthen the evidence available for implementation of ART delivery in Africa.
BMC Infectious Diseases, 2015
Background: In sub-Saharan Africa (SSA), antiretroviral therapy (ART) can prolong life for HIV-infected patients. However, patients initiating ART, especially in routine treatment programs, commonly dropout from care either due to death or loss to follow-up. Methods: In a cohort of HIV-infected patients initiating ART at a public sector clinic in Uganda, we assessed predictors of dropout from care (a composite outcome combining death and loss to follow-up). From a large set of socio-demographic, clinical, and laboratory variables routinely collected at ART initiation, we selected those predicting dropout at P <0.1 in unadjusted analyses for inclusion into a multivariable proportional hazards regression model. We then used a stepwise backward selection procedure to identify variables which independently predicted dropout at P <0.05. Results: Data from 5,057 patients were analyzed. The median age was 33 years (IQR 28 to 40) and 27.4 % had CD4+ T-cell counts <100 cells/μL at ART initiation. The median duration of follow-up was 24 months (IQR = 14 to 42, maximum follow-up = 64 months). Overall dropout was 26.9 % (established cumulative mortality = 2.3 %, loss to follow-up = 24.6 %), 5.6 % were transferred to other service providers, and 67.5 % were retained in care. A diagnosis of Kaposi's sarcoma (hazard ratio (HR) = 3.3, 95 % CI 2.5 to 4.5); HIV-associated dementia (HR = 2.6, 95 % CI 1.5 to 4.6); history of cryptococcosis (HR = 2.2, 95 % CI 1.4 to 3.3); and reduced hemoglobin concentration (<11 g/dl versus ≥13.8 g/dl (HR = 1.9, 95 % CI 1.6 to 2.2) were strong predictors of dropout. Other independent predictors of dropout were: year of ART initiation; weight loss ≥10 %; reduced total lymphocyte count; chronic diarrhea; male sex; young age (≤28 years); and marital status. Conclusions: Among HIV-infected patients initiating ART at a public sector clinic in SSA, biological factors that usually predict death were especially predictive of dropout. As most of the dropouts were lost to follow-up, this observation suggests that many losses to follow-up may have died. Future studies are needed to identify appropriate interventions that may improve both individual-level patient outcomes and outcome ascertainment among HIV-infected ART initiators in this setting.
BMJ open, 2018
The aim of this study was to use a sampling-based approach to obtain estimates of retention in HIV care before initiation of antiretroviral treatment (ART), corrected for outcomes in patients who were lost according to clinic registers. Retrospective cohort study of HIV-positive individuals not yet eligible for ART (CD4 >500). Three urban and three rural HIV care clinics in Uganda; information was extracted from the clinic registers for all patients who had registered for pre-ART care between January and August 2015. A random sample of patients who were lost according to the clinic registers (>3 months late to scheduled visit) was traced to ascertain their outcomes. The proportion of patients lost from care was estimated using a competing risks approach, first based on the information in the clinic records alone and then using inverse probability weights to incorporate the results from tracing. Cox regression was used to determine factors associated with loss from care. Of 115...
Loss to Clinic and Five-Year Mortality among HIV-Infected Antiretroviral Therapy Initiators
PLoS ONE, 2014
Missing outcome data due to loss to follow-up occurs frequently in clinical cohort studies of HIV-infected patients. Censoring patients when they become lost can produce inaccurate results if the risk of the outcome among the censored patients differs from the risk of the outcome among patients remaining under observation. We examine whether patients who are considered lost to follow up are at increased risk of mortality compared to those who remain under observation. Patients from the US Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) who newly initiated combination antiretroviral therapy between January 1, 1998 and December 31, 2009 and survived for at least one year were included in the study. Mortality information was available for all participants regardless of continued observation in the CNICS. We compare mortality between patients retained in the cohort and those lost-to-clinic, as commonly defined by a 12-month gap in care. Patients who were considered lost-to-clinic had modestly elevated mortality compared to patients who remained under observation after 5 years (risk ratio (RR): 1.2; 95% CI: 0.9, 1.5). Results were similar after redefining lossto-clinic as 6 months (RR: 1.0; 95% CI: 0.8, 1.3) or 18 months (RR: 1.2; 95% CI: 0.8, 1.6) without a documented clinic visit. The small increase in mortality associated with becoming lost to clinic suggests that these patients were not lost to care, rather they likely transitioned to care at a facility outside the study. The modestly higher mortality among patients who were lostto-clinic implies that when we necessarily censor these patients in studies of time-varying exposures, we are likely to incur at most a modest selection bias. Citation: Edwards JK, Cole SR, Westreich D, Moore R, Mathews C, et al. (2014) Loss to Clinic and Five-Year Mortality among HIV-Infected Antiretroviral Therapy Initiators. PLoS ONE 9(7): e102305.
BMC Medical Informatics and Decision Making, 2016
Background: While, lost to follow-up (LTFU) from antiretroviral therapy (ART) can be considered a catch-all category for patients who miss scheduled visits or medication pickups , operational definitions and methods for defining LTFU vary making comparisons across programs challenging. Using weekly cutoffs , we sought to determine the probability that an individual would return to clinic given that they had not yet returned in order to identify the LTFU cutoff that could be used to inform clinical management and tracing procedures. Methods: Individuals who initiated ART with Dignitas International supported sites (n = 22) in Zomba, Malawi between January 1 2007-June 30 2010 and were ≥ 1 week late for a follow-up visit were included. Lateness was categorized using weekly cutoffs from ≥1 to ≥26 weeks late. At each weekly cutoff , the proportion of patients who returned for a subsequent follow-up visit were identified. Cumulative Distribution Functions (CDFs) were plotted to determine the probability of returning as a function of lateness. Hazard functions were plotted to demonstrate the proportion of patients who returned each weekly interval relative to those who had yet to return. Results: In total, n = 4484 patients with n = 7316 follow-up visits were included. The number of included follow-up visits per patient ranged from 1-10 (median: 1). Both the CDF and hazard function demonstrated that after being ≥9 weeks late, the proportion of new patients who returned relative to those who had yet to return decreased substantially. Conclusions: We identified a LTFU definition useful for clinical management. The simple functions plotted here did not require advanced statistical expertise and were created using Microsoft Excel, making it a particularly practical method for HIV programs in resource-constrained settings.