Measures of Longitudinal Immune Dysfunction and Risk of AIDS and Non-AIDS Defining Malignancies in Antiretroviral-Treated People With Human Immunodeficiency Virus.

BACKGROUND: Human immunodeficiency virus (HIV) infection leads to chronic immune activation/inflammation that can persist in virally suppressed persons on fully active antiretroviral therapy (ART) and increase risk of malignancies. The prognostic role of low CD4:CD8 ratio and elevated CD8 cell counts on the risk of cancer remains unclear. METHODS: We investigated the association of CD4:CD8 ratio on the hazard of non-AIDS defining malignancy (NADM), AIDS-defining malignancy (ADM) and most frequent group of cancers in ART-treated people with HIV (PWH) with a CD4 and CD8 cell counts and viral load measurements at baseline. We developed Cox proportional hazard models with adjustment for known confounders of cancer risk and time-dependent cumulative and lagged exposures of CD4:CD8 ratio to account for time-evolving risk factors and avoid reverse causality. RESULTS: CD4:CD8 ratios below 0.5, compared to above 1.0, were independently associated with a 12-month time-lagged higher risk of ADM and infection-related malignancies (adjusted hazard ratio 2.61 [95% confidence interval {CI }1.10-6.19] and 2.03 [95% CI 1.24-3.33], respectively). CD4 cell counts below 350 cells/µL were associated with an increased risk of NADMs and ADMs, as did infection, smoking, and body mass index-related malignancies. CONCLUSIONS: In ART-treated PWH low CD4:CD8 ratios were associated with ADM and infection-related cancers independently from CD4 and CD8 cell counts and may alert clinicians for cancer screening and prevention of NADM.

Trends in Cancer Incidence in Different Antiretroviral Treatment-Eras amongst People with HIV.

Despite cancer being a leading comorbidity amongst individuals with HIV, there are limited data assessing cancer trends across different antiretroviral therapy (ART)-eras. We calculated age-standardised cancer incidence rates (IRs) from 2006-2021 in two international cohort collaborations (D:A:D and RESPOND). Poisson regression was used to assess temporal trends, adjusted for potential confounders. Amongst 64,937 individuals (31% ART-naïve at baseline) and 490,376 total person-years of follow-up (PYFU), there were 3763 incident cancers (IR 7.7/1000 PYFU [95% CI 7.4, 7.9]): 950 AIDS-defining cancers (ADCs), 2813 non-ADCs, 1677 infection-related cancers, 1372 smoking-related cancers, and 719 BMI-related cancers (groups were not mutually exclusive). Age-standardised IRs for overall cancer remained fairly constant over time (8.22/1000 PYFU [7.52, 8.97] in 2006-2007, 7.54 [6.59, 8.59] in 2020-2021). The incidence of ADCs (3.23 [2.79, 3.72], 0.99 [0.67, 1.42]) and infection-related cancers (4.83 [4.2, 5.41], 2.43 [1.90, 3.05]) decreased over time, whilst the incidence of non-ADCs (4.99 [4.44, 5.58], 6.55 [5.67, 7.53]), smoking-related cancers (2.38 [2.01, 2.79], 3.25 [2.63-3.96]), and BMI-related cancers (1.07 [0.83, 1.37], 1.88 [1.42, 2.44]) increased. Trends were similar after adjusting for demographics, comorbidities, HIV-related factors, and ART use. These results highlight the need for better prevention strategies to reduce the incidence of NADCs, smoking-, and BMI-related cancers.

Integrase Strand Transfer Inhibitor Use and Cancer Incidence in a Large Cohort Setting.

BACKGROUND: Limited data exist examining the association between incident cancer and cumulative integrase inhibitor (INSTI) exposure. METHODS: Participants were followed from baseline (latest of local cohort enrollment or January 1, 2012) until the earliest of first cancer, final follow-up, or December 31, 2019. Negative binomial regression was used to assess associations between cancer incidence and time-updated cumulative INSTI exposure, lagged by 6 months. RESULTS: Of 29 340 individuals, 74% were male, 24% were antiretroviral treatment (ART)-naive, and median baseline age was 44 years (interquartile range [IQR], 36-51). Overall, 13 950 (48%) individuals started an INSTI during follow-up. During 160 657 person-years of follow-up ([PYFU] median 6.2; IQR, 3.9-7.5), there were 1078 cancers (incidence rate [IR] 6.7/1000 PYFU; 95% confidence interval [CI], 6.3-7.1). The commonest cancers were non-Hodgkin lymphoma (n = 113), lung cancer (112), Kaposi's sarcoma (106), and anal cancer (103). After adjusting for potential confounders, there was no association between cancer risk and INSTI exposure (≤6 months vs no exposure IR ratio: 1.15 [95% CI, 0.89-1.49], >6-12 months; 0.97 [95% CI, 0.71-1.32], >12-24 months; 0.84 [95% CI, 0.64-1.11], >24-36 months; 1.10 [95% CI, 0.82-1.47], >36 months; 0.90 [95% CI, 0.65-1.26] [P = .60]). In ART-naive participants, cancer incidence decreased with increasing INSTI exposure, mainly driven by a decreasing incidence of acquired immune deficiency syndrome cancers; however, there was no association between INSTI exposure and cancer for those ART-experienced (interaction P < .0001). CONCLUSIONS: Cancer incidence in each INSTI exposure group was similar, despite relatively wide CIs, providing reassuring early findings that increasing INSTI exposure is unlikely to be associated with an increased cancer risk, although longer follow-up is needed to confirm this finding.

Uptake and Discontinuation of Integrase Inhibitors (INSTIs) in a Large Cohort Setting.

BACKGROUND: Despite increased integrase strand transfer inhibitor (INSTI) use, limited large-scale, real-life data exists on INSTI uptake and discontinuation. SETTING: International multicohort collaboration. METHODS: RESPOND participants starting dolutegravir (DTG), elvitegravir (EVG), or raltegravir (RAL) after January 1, 2012 were included. Predictors of INSTI used were assessed using multinomial logistic regression. Kaplan-Meier and Cox proportional hazards models describe time to and factors associated with discontinuation. RESULTS: Overall, 9702 persons were included; 5051 (52.1%) starting DTG, 1933 (19.9%) EVG, and 2718 (28.0%) RAL. The likelihood of starting RAL or EVG vs DTG decreased over time and was higher in Eastern and Southern Europe compared with Western Europe. At 6 months after initiation, 8.9% (95% confidence interval: 8.3% to 9.5%) had discontinued the INSTI (6.4% DTG, 7.4% EVG, and 14.0% RAL). The main reason for discontinuation was toxicity (44.2% DTG, 42.5% EVG, 17.3% RAL). Nervous system toxicity accounted for a higher proportion of toxicity discontinuations on DTG (31.8% DTG, 23.4% EVG, 6.6% RAL). Overall, treatment simplification was highest on RAL (2.7% DTG, 1.6% EVG, and 19.8% RAL). Factors associated with a higher discontinuation risk included increasing year of INSTI initiation, female gender, hepatitis C coinfection, and previous non-AIDS-defining malignancies. Individuals in Southern and Eastern Europe were less likely to discontinue. Similar results were seen for discontinuations after 6 months. CONCLUSIONS: Uptake of DTG vs EVG or RAL increased over time. Discontinuation within 6 months was mainly due to toxicity; nervous system toxicity was highest on DTG. Discontinuation was highest on RAL, mainly because of treatment simplification.

Modeling and analysis of Gleason score 8-10 prostate cancers in the REDUCE study.

OBJECTIVE: To explore explanations for the numerical imbalance of biopsy-detected Gleason 8-10 prostate cancers (PCa) diagnosed in years 3-4 in the dutasteride and placebo groups of the Reduction by Dutasteride of Prostate Cancer Events (REDUCE) study. METHODS: REDUCE was a 4-year, randomized, double-blind, placebo-controlled trial of dutasteride (0.5 mg/d) vs placebo for PCa risk reduction. We modeled the incidence of Gleason 8-10 cancer and used logistic regression analysis to evaluate the effects of baseline predictors of PCa, as well as post-baseline prostate volume at the time of biopsy, on PCa diagnosis. We compared needle biopsy Gleason scores with corresponding surgery Gleason scores. All statistical tests conducted were 2-sided. RESULTS: Had there been a scheduled biopsy occurring only at year 4, we estimated a similar incidence of Gleason 8-10 PCa in the dutasteride (n = 45) and placebo (n = 46) groups. Two biopsy Gleason 7 cancers in the placebo group (n = 150) were upgraded to Gleason 8-10 cancer on prostatectomy, and no patients in the dutasteride group (n = 111) were upgraded. Logistic regression analysis demonstrated the effect of prostate volume on Gleason 8-10 cancer diagnosis. CONCLUSION: Although modeling of REDUCE data showed a similar incidence of Gleason 8-10 cancer in the dutasteride and placebo groups at year 4, an association between dutasteride and Gleason 8-10 cancer cannot be definitely excluded. It is likely that several biases, notably study design and prostate size at the time of biopsy, contributed to the numerical imbalance in Gleason 8-10 cancers observed between the treatment groups in years 3-4.