METHODS: Incidence of malignancy after cohort enrollment was evaluated. Factors associated with development of hematological and nonhematological malignancy were analyzed using competing risk regression and survival time using Kaplan-Meier.
RESULTS: Of 7455 patients, 107 patients (1%) developed a malignancy: 34 (0.5%) hematological [0.08 per 100 person-years (/100PY)] and 73 (1%) nonhematological (0.17/100PY). Of the hematological malignancies, non-Hodgkin lymphoma was predominant (n = 26, 76%): immunoblastic (n = 6, 18%), Burkitt (n = 5, 15%), diffuse large B-cell (n = 5, 15%), and unspecified (n = 10, 30%). Others include central nervous system lymphoma (n = 7, 21%) and myelodysplastic syndrome (n = 1, 3%). Nonhematological malignancies were mostly Kaposi sarcoma (n = 12, 16%) and cervical cancer (n = 10, 14%). Risk factors for hematological malignancy included age >50 vs. ≤30 years [subhazard ratio (SHR) = 6.48, 95% confidence interval (CI): 1.79 to 23.43] and being from a high-income vs. a lower-middle-income country (SHR = 3.97, 95% CI: 1.45 to 10.84). Risk was reduced with CD4 351-500 cells/µL (SHR = 0.20, 95% CI: 0.05 to 0.74) and CD4 >500 cells/µL (SHR = 0.14, 95% CI: 0.04 to 0.78), compared to CD4 ≤200 cells/µL. Similar risk factors were seen for nonhematological malignancy, with prior AIDS diagnosis showing a weak association. Patients diagnosed with a hematological malignancy had shorter survival time compared to patients diagnosed with a nonhematological malignancy.
CONCLUSIONS: Nonhematological malignancies were common but non-Hodgkin lymphoma was more predominant in our cohort. PLHIV from high-income countries were more likely to be diagnosed, indicating a potential underdiagnosis of cancer in low-income settings.
METHODS: Participants who were enrolled between January 2003 and March 2019 in a regional Asia HIV cohort with weight and height measurements prior to antiretroviral therapy (ART) initiation were included. Factors associated with mean CD4 increase were analysed using repeated-measures linear regression. Time to first VF after 6 months on ART and time to first development of CVD risk markers were analysed using Cox regression models. Sensitivity analyses were done adjusting for Asian BMI thresholds.
RESULTS: Of 4993 PLHIV (66% male), 62% had pre-treatment BMI in the normal range (18.5-25.0 kg/m2 ), while 26%, 10% and 2% were underweight ( 30 kg/m2 ), respectively. Both higher baseline and time-updated BMI were associated with larger CD4 gains compared with normal BMI. After adjusting for Asian BMI thresholds, higher baseline BMIs of 23-27.5 and > 27.5 kg/m2 were associated with larger CD4 increases of 15.6 cells/µL [95% confidence interval (CI): 2.9-28.3] and 28.8 cells/µL (95% CI: 6.6-50.9), respectively, compared with normal BMI (18.5-23 kg/m2 ). PLHIV with BMIs of 25-30 and > 30 kg/m2 were 1.27 times (95% CI: 1.10-1.47) and 1.61 times (95% CI: 1.13-2.24) more likely to develop CVD risk factors. No relationship between pre-treatment BMI and VF was observed.
CONCLUSIONS: High pre-treatment BMI was associated with better immune reconstitution and CVD risk factor development in an Asian PLHIV cohort.