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The Effect of Monitoring Viral Load and Tracing Patients Lost to Follow-up on the Course of the HIV Epidemic in Malawi: A Mathematical Model.

ABSTRACT: Antiretroviral therapy (ART) reduces HIV transmission, but treated patients may again become infectious. We used a mathematical model to determine whether ART as prevention is more effective if viral load (VL) is routinely monitored and patients lost to follow-up (LTFU) traced.We simulated ART cohorts to parameterize a deterministic transmission model calibrated to Malawi. We investigated the following strategies for improving treatment and retention: monitoring VL every 12 or 24 months, tracing patients LTFU, or a generic strategy leading to uninterrupted treatment. We tested 3 scenarios, where ART scale-up continues at current (Universal ART), reduced (Failed scale-up), or accelerated speed (Test&Treat).In the Universal ART scenario, between 2017 and 2020 (2050), monitoring VL every 24 months prevented 0.5% (0.9%), monitoring every 12 months prevented 0.8% (1.4%), tracing prevented 0.3% (0.5%), and uninterrupted treatment prevented 5.5% (9.9%) of HIV infections. Failed scale-up resulted in 25% more infections than the Universal ART scenarios, whereas Test&Treat resulted in 7%-8% less.Test&Treat reduces transmission of HIV, despite individual cases of treatment failure and ART interruption. Whereas viral load monitoring and tracing have only a minor impact on transmission, interventions that aim to minimize treatment interruptions can further increase the preventive effect of ART.

SUBMITTER: Estill J

PROVIDER: S-EPMC6007424 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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The Effect of Monitoring Viral Load and Tracing Patients Lost to Follow-up on the Course of the HIV Epidemic in Malawi: A Mathematical Model.

Estill Janne J Kerr Cliff C CC Blaser Nello N Salazar-Vizcaya Luisa L Tenthani Lyson L Wilson David P DP Keiser Olivia O

Open forum infectious diseases 20180427 5

<h4>Background</h4>Antiretroviral therapy (ART) reduces HIV transmission, but treated patients may again become infectious. We used a mathematical model to determine whether ART as prevention is more effective if viral load (VL) is routinely monitored and patients lost to follow-up (LTFU) traced.<h4>Methods</h4>We simulated ART cohorts to parameterize a deterministic transmission model calibrated to Malawi. We investigated the following strategies for improving treatment and retention: monitorin ...[more]

PMID: 29977952

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Project description:Long-term outcome studies are frequently hindered by a decreasing frequency of patient follow-up with the treating surgeon over time. Whether this attrition represents a "loss of faith" in their index surgeon or the realities of a geographically mobile society has never been assessed in a population of patients undergoing spinal surgery. The purpose of this article is to determine the frequency with which patients who have undergone prior surgery and develop new problems attempt to follow-up with their index spine surgeon. The study design was a population survey. All patients seen at two university-based spine centers over a 3-month period were surveyed regarding prior spine surgery. The questionnaire asked details of the previous operation, whether the patient had sought follow-up with their index surgeon, why the patient did not continue treatment with that surgeon, and whether the patient was satisfied with their prior treatment. Sixty-nine patients completed the survey. Prior operations were lumbar (53 patients) and cervical (16). When asked the reason for not seeing their prior surgeon, 10 patients (15%) stated that they (the patient) had moved and 16 (23%) responded that their surgeon no longer practiced in the area. Thirteen (19%) were unhappy with their previous care, 22 (32%) were seeking a second opinion, and 7 (10%) were told they needed more complex surgery. Thirty-seven (54%) discussed their symptoms with their original surgeon before seeking another surgeon. Although 32 patients (46%) had not discussed their new complaints with their index surgeon, only 3 patients (4%) chose not to return to their prior surgeon despite having the opportunity to do so. Forty-nine patients (71%) were satisfied with their prior surgical care, and 42 patients (61%) would undergo the index operation again. Most of the patients seen at the authors' practices after undergoing prior spine surgery elsewhere failed to follow up with their prior spine surgeon for geographical reasons. It appears that the majority of patients who develop new spinal complaints will seek out their treating surgeon when possible. This suggests that patient attrition over long-term follow-up may reflect a geographically mobile population rather than patient dissatisfaction with prior treatment.

Project description:BackgroundIncomplete ascertainment of outcomes in randomized controlled trials (RCTs) is likely to bias final study results if reasons for unavailability of patient data are associated with the outcome of interest. The primary objective of this study is to assess the potential impact of loss to follow-up on the estimates of treatment effect. The secondary objectives are to describe, for published RCTs, (1) the reporting of loss to follow-up information, (2) the analytic methods used for handling loss to follow-up information, and (3) the extent of reported loss to follow-up.MethodsWe will conduct a systematic review of reports of RCTs recently published in five top general medical journals. Eligible RCTs will demonstrate statistically significant effect estimates with respect to primary outcomes that are patient-important and expressed as binary data. Teams of 2 reviewers will independently determine eligibility and extract relevant information from each eligible trial using standardized, pre-piloted forms. To assess the potential impact of loss to follow-up on the estimates of treatment effect we will, for varying assumptions about the outcomes of participants lost to follow-up (LTFU), calculate (1) the percentage of RCTs that lose statistical significance and (2) the mean change in effect estimate across RCTs. The different assumptions we will test are the following: (1) none of the LTFU participants had the event; (2) all LTFU participants had the event; (3) all LTFU participants in the treatment group had the event; none of those in the control group had it (worst case scenario); (4) the event incidence among LTFU participants (relative to observed participants) increased, with a higher relative increase in the intervention group; and (5) the event incidence among LTFU participants (relative to observed participants) increased in the intervention group and decreased in the control group.DiscussionWe aim to make our objectives and methods transparent. The results of this study may have important implications for both clinical trialists and users of the medical literature.

Dataset Information

The Effect of Monitoring Viral Load and Tracing Patients Lost to Follow-up on the Course of the HIV Epidemic in Malawi: A Mathematical Model.

Publications

The Effect of Monitoring Viral Load and Tracing Patients Lost to Follow-up on the Course of the HIV Epidemic in Malawi: A Mathematical Model.

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