Lung Cancer Screening in People Living with HIV: Modeling to Bridge the Evidence

Lung cancer is the leading cause of cancer death in the U.S., both among people living with HIV (PLHIV)¹ and in the general population. In 2011 the National Lung Screening Trial (NLST) showed that annual screening by low-dose computed tomography (CT) reduces lung cancer mortality by 20% among heavy smokers,² and the U.S. Preventive Services Task Force (USPSTF) now recommends screening for current and former smokers aged 55-80 with at least 30 pack-years and no more than 15 quit-years. Centers for Medicare and Medicaid Services (CMS) guidelines are similar but end screening at age 77.

PLHIV have elevated lung cancer incidence and mortality compared to the general population, both due to increased smoking prevalence and an independent effect of immunosuppression. Therefore, CT screening would be expected to be beneficial, but harms could also be more frequent. In this issue of AIDS, Kong et al. apply a simulation modeling approach to quantify these benefits and harms in PLHIV across a range of potential screening scenarios.³ This is the best approach to comprehensively study screening in PLHIV since a large randomized trial is not feasible.

Kong et al. adapted the Lung Cancer Policy Model (LCPM), which helped inform current USPSTF guidelines,⁴ for the setting of HIV. The adapted model simulates life histories of immunocompetent (CD4≥500 cells/μL) HIV-infected men and women from age 40 to death, using 100% ART adherence in the primary analysis but 80% adherence in a sensitivity analysis. The screening benefits (lung cancer mortality reduction and life-years gained) and the harms (e.g. false-positives, overdiagnosis) are then calculated for different annual screening scenarios that vary the pack-year eligibility, age-to-start screening, and age-to-stop.

Of multiple screening strategies found to be efficient, Kong et al. highlight that CMS screening criteria (age 55-77, 30 pack-years, 15 or fewer quit-years) applied among PLHIV would be expected to produce an 18.9% reduction in lung cancer mortality among those screened. Encouragingly, this approached the 22.7% reduction they found for HIV-uninfected individuals. It also approximates the mortality reduction in the NLST (20.0%), but a direct comparison is difficult since NLST participants underwent only 3 annual screens while Kong et al. simulated continual annual screening. Other strategies also fell on the efficiency frontier, which was constructed using the tradeoff between the lung cancer mortality reduction and the number of CT exams.

Though average life expectancy among PLHIV has made dramatic gains, it remains reduced compared to the general population.⁵ Thus, CT screening at the same ages would be expected to save fewer life-years in a population of PLHIV compared to HIV-uninfected individuals, even if the reduction in lung cancer mortality is similar. Indeed, for the CMS strategy, Kong et al. found that PLHIV gained 20% fewer life-years compared to HIV-uninfected individuals. Similarly, when ART adherence was reduced from 100% to 80% (thus increasing competing causes of death), the life-years gained were reduced by an additional 18%. Thus, providers should carefully assess overall health status and ART adherence when considering CT screening for individual HIV patients, as screening is not advised for individuals who have limited life expectancy or cannot undergo curative surgery.

After adjusting for differences in population age structure, lung cancers in PLHIV are diagnosed 4 years earlier than those in the general population,⁶ so beginning screening at earlier ages could be an efficient strategy. Of five strategies found to be on the efficiency frontier by Kong et al., one began at age 50 and one at 45, but these led to many more screens per individual than strategies beginning at age 55. As in HIV-uninfected individuals, a lengthened screening interval for individuals with negative or otherwise low-risk initial CT results might reduce this burden, but requires further study.

Kong et al. appropriately restricted models to ART-adherent PLHIV with a CD4 count of at least 500 cells/μL, who are most likely to benefit from screening. Future analyses might address whether other PLHIV should be considered for screening as well, since some patients will not reach a CD4≥500 even with complete ART adherence. Unfortunately, only about one-quarter of the U.S. HIV-infected population is diagnosed, retained in care, on ART, and virally suppressed,⁷ so improvements along the HIV care continuum would be necessary to extend CT screening to a majority of PLHIV. In the general population, there is substantial momentum toward selecting individuals for lung screening based on continuous risk prediction (instead of broad categories) to improve effectiveness and efficiency.⁸ This approach could also be useful for PLHIV, but will require development and validation of HIV-specific lung cancer risk models that account for risk factors such as CD4 count, CD4/CD8 ratio, and HIV RNA concentration.⁹

Concerns also remain regarding excess harms of screening in PLHIV; for example, rates of complications may be increased after surgical resection of early-stage tumors¹⁰ though not after lung biopsy.¹¹ Very immunosuppressed patients may have more frequent false-positive CT results,¹² but these individuals should not be screened in general due to low likelihood of net benefit. Few data exist to quantify the risk of radiation-induced cancers specifically among PLHIV, or to describe any unique psychological consequences of the screening process in this population that already faces a high burden of medical surveillance. It is also possible that non-cancer smoking-related conditions may be incidentally diagnosed during CT screening more frequently among PLHIV.

The analysis by Kong et al. takes an important step to demonstrate that CT screening could benefit PLHIV by reducing the elevated risk of lung cancer mortality. Empirical outcomes of screening in this group are poorly described, and the field needs additional studies to inform best practices for screening eligibility and exclusion and for avoiding excess harm. Development of communication methods and decision tools that are appropriate for PLHIV will be critical to enable high-quality shared decision-making. Finally, alongside our enthusiasm to save lives by detecting lung cancers early, we must continue to emphasize that quitting smoking remains the best way to prevent lung cancer death regardless of HIV status.