Research Project

Assessing the quality of life and its relation to treatment outcomes among patients with HIV-associated lymphoma at the Uganda Cancer Institute.

Malignancies have become the leading cause of morbidity and mortality in people with HIV (PWH) as their life expectancy has improved in the antiretroviral therapy (ART) era. Lymphoma remains a common malignancy in PWH, particularly in sub-Saharan Africa. A diagnosis of both HIV and cancer is particularly devastating. Among patients with HIV and cancer, a study done at Duke University found that the 27 participants drew strong parallels between being diagnosed with HIV and cancer. Many described HIV-related stigma that hindered social support. Cancer treatment side effects were a major challenge, impacting treatment adherence for both cancer and HIV. To address the many important psycho-social challenges that persons with HIV and cancer face, we seek to do quality-of-life (QOL) assessments and their relationship to treatment outcomes. This information will: 1) bridge the knowledge gap on the pre-and post-treatment QOL of patients with HIV-related lymphomas at the UCI; 2) allow us to determine whether pre-treatment QOL predicts response to treatment and OS at 1 year as has been reported in HIC, potentially instituting measures to improve QOL such as nutritional, psychological, and pharmaceutical measures; 3) advocate for evaluation of pre-and post-treatment QOL for every cancer registered at the UCI as routine metric to improve care and foster further studies. Methods. This will be a prospective cohort study that will employ both qualitative and quantitative methodology conducted at the Uganda Cancer Institute. I intend to leverage a prospective lymphoma cohort to evaluate the quality of life in this population. All patients enrolled in the cohort will be eligible and those who provide informed consent will be interviewed. An interview will be conducted by the study team using the Functional Assessment of Cancer Therapy – lymphoma (FACT-lym) to assess for QOL. There will be two interviews conducted, at the initiation of treatment and after completion of therapy to assess the role of QOL in predicting treatment outcome. Data will be analyzed by the statistical software STATA version 16.0. Descriptive statistics will be used to show the quality of life of patients with HIV-related lymphomas at diagnosis and the end of treatment at the UCI. We shall use a t-test to compare mean QOL scores at diagnosis and the end of treatment. For normally distributed numeric variables, paired t-tests will be used and if they are not normally distributed, Mann-Whitney analysis will be performed. A chi-square test will be conducted for categorical variables. The confidence interval will be 95%. Logistic regression models will be used to evaluate QOL scores and outcomes (complete response, partial response, stable disease, and progressive disease) Cox proportional hazards models will be used to assess the association between QOL and overall survival. Overall survival (OS) will be defined as the time from disease diagnosis to death due to any cause.

Research Significance

QOL scores and performance scale scores have been shown to predict the outcome of patients with cancer. Performance status is defined as a measure of how well a patient can perform ordinary tasks and carry out daily activities (18) Physical functioning is a key component of quality of life, and it is usually assessed by using performance status (PS) scales such as the Eastern Cooperative Oncology Group Scale. Some studies have shown the prognostic importance of PS in cancer outcomes. A clinical trial compared the prognostic value for overall survival (OS) of the WHO PS to the baseline physical function scale of the European Organization for the Research and Treatment of Cancer and the Functional Assessment of Chronic Illness Therapy (EORTC QLQ-C30 (QLQ-C30 PF) in a prospective randomized phase 3 trial in advanced colorectal cancer (ACC), the CAIRO study. The study concluded that PF, as assessed by patients using the EORTC QLQ-C30, is superior in terms of prognostic value to WHO PS as scored by physicians (19). Therefore, in this study, QOL scores will be used to predict outcomes, not performance scale scores. Several studies have been done to assess the quality of life of patients with HIV and that of patients with lymphoma, but few have been done among patients with HIV-related lymphomas. Only a few studies have assessed QOL of patients with HIV-related lymphomas, and none in sub-Saharan Africa (SSA). Researchers at the University of California found that patients with HIV-associated NHL had a worse QOL and survival than HIV-negative patients due to a combination of co-morbidity, aggressive histology, and lack of social support (20). A study at the Mayo Clinic used the Functional Assessment of Cancer Therapy – General (FACT-G) to predict event-free survival and overall survival (OS) of HIV-positive patients diagnosed with aggressive lymphoma over eight years. All baseline QOL measures except emotional well-being were significantly associated with OS of which all, but Linear Analogue Self-Assessment (LASA) spiritual remained significant after adjusting for IPI and NHL subtype. The strongest associations were with total FACT‐G and functional well-being. QOL LASA was associated with OS. Patients with a QOL ≤50 had a median OS of 92 months compared with 121 months for patients with QOL >50. In a study of patients with aggressive lymphoma without HIV pretreatment, QoL predicted OS in multivariate analysis. The literature search yielded no data on the quality of life of patients with lymphoma or HIV-associated lymphoma in Uganda or any country in SSA While managing patients with HIV-related lymphoma at the Uganda Cancer Institute (UCI), we have observed that many patients are in a poor state of health as assessed by performance status (PS) and have a poor QOL before treatment. When they achieve remission with chemotherapy, there is generally an improvement in PS and an improvement in their QOL. However, these clinical observations of QOL changes have not been documented with any standard tool using patient-reported metrics. Moreover, we do not know whether the patient’s QOL at the initiation of treatment predicts treatment outcome and OS as reported for patients in a high-income country (HIC) with aggressive lymphoma. Therefore, in this study, we aim to assess the QOL of patients with HIV-related lymphomas before and following treatment and determine whether their pre-treatment QOL predicts their response to treatment and OS. This information will: 1) bridge the knowledge gap on the pre-and post-treatment QOL of patients with HIV-related lymphomas at the UCI; 2) allow us to determine whether pre-treatment QOL predicts response to treatment and OS at 1 year as has been reported in HIC, potentially instituting measures to improve QOL such as nutritional, psychological, and pharmaceutical measures; 3) advocate for evaluation of pre-and post-treatment QOL for every cancer registered at the UCI as routine metric to improve care.

Publications

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Mentors

• • John Harlan, MD
  • Adelline Twimukye, BASS, MPAM
  • Warren Phipps, MD, MPH

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