The overall goal of this project is to improve the management of HIV infected (HIV+) lung cancer patients. Lung cancer is the leading cause of cancer death in older HIV+ patients. Up to 30% of lung cancer cases are diagnosed at a loco-regional stage (with expected increases due to the implementation of lung cancer screening in the HIV+ population), can be treated with a curative intent, and may experience relatively good long-term survival. Despite this, HIV+ lung cancer patients experience lung cancer treatment disparities and have poorer lung cancer outcomes. The risk/benefit ratio of cancer therapies can be substantially altered in HIV+ patients because of differences in treatment toxicity, tumor aggressiveness, functional status, life expectancy, and quality of life. Unfortunately, patients with comorbidities such as HIV are consistently excluded from randomized controlled trials (RCTs) generating an important gap in knowledge regarding their management. Lack of data relevant to HIV+ patients has profound negative impact including under treatment, increased morbidity, and decreased survival. Thus, optimizing the management of HIV+ lung cancer patients is a major public health priority. In this study, we will use simulation modeling, an approach complementary to RCTs, to determine the optimal treatment of early stage HIV+ lung cancer patients.
The Specific Aims are to: 1) enhance and validate the Lung Cancer Policy Model (LCPM) to simulate the management and subsequent outcomes of HIV+ patients with loco-regional non-small cell lung cancer (NSCLC); 2) determine the optimal management for stage I NSCLC in HIV+ patients; 3) find the optimal indications for adjuvant chemotherapy for stage II-IIIA NSCLC in HIV+ patients; and 4) identify optimal management strategies for stage I-IIIA NSCLC in HIV+ patients with severe cardiac, pulmonary, renal or hepatic comorbidities. To achieve these Aims, we will use an enhanced version of the LCPM, a well-validated mathematical model of lung cancer progression.
In Aim 1, we will use data from several population-based HIV+ cohorts to substantially enhance, calibrate, and validate the LCPM by incorporating an HIV natural history module, as well as HIV-specific parameter modifications for functional status, frailty, cancer treatments, complications of surgery and chemotherapy toxicity, outcomes, survival and quality of life. Then, we will assess the optimal management, in terms of reducing toxicity and maximizing survival and quality of life, of HIV+ patients with early stage lung cancer. Our study is innovative in providing HIV-specific cancer treatment guidance, as well as in applying modeling approaches mostly used to evaluate cancer screening, to the optimization of lung cancer therapies. The results of the study will directly inform the management of large numbers of HIV+ lung cancer patients, a vulnerable and understudied group that currently experience substantially worse outcomes.
The objective of this study is to improve the management and outcomes of HIV+ patients with loco-regional lung cancer. Towards this end, we will use the Lung Cancer Policy Model, a validated micro simulation model, to perform comparative effective analyses tailored to this population. Our results will identify the optimal lung cancer management for HIV infected lung cancer patients to reduce treatment toxicities and maximize survival and quality of life.
| Thaler, Jonathan; Sigel, Carlie; Beasley, Mary Beth et al. (2017) Clinically significant mutations in HIV-infected patients with lung adenocarcinoma. Br J Cancer 117:1392-1395 |
