Gynaecologic and breast cancers in women living with HIV in South Africa: A record linkage study.

Breast and gynaecologic cancers account for approximately half of all cancers diagnosed amongst women in South Africa, many of whom also live with HIV. We aimed to determine the incidence of and risk factors for developing breast and gynaecologic cancers in women living with HIV (WLHIV) in South Africa. This is a longitudinal analysis of the South African HIV Cancer Match study including women aged ≥15 years with two or more HIV-related laboratory tests. We used Cox proportional hazard models to determine the association of Human Papilloma Virus (HPV)-related and hormone-related gynaecologic cancer with patient- and municipal-level characteristics. From 3 447 908 women and 10.5 million years of follow-up, we identified 11 384 incident and 7612 prevalent gynaecologic and breast cancers. The overall crude incidence rate was 108/1 00 000 person-years (pyears) (95% confidence interval [CI]: 106-110), with the highest incidence observed for cervical cancer (70/1 00 000 pyears; 95% CI: 68.5-71.7). Low CD4 cell counts and high HIV RNA viral loads increased the risk of cervical and other HPV-related cancers. Age was associated with both HPV-related and hormone-related cancers. Women accessing health facilities in high socioeconomic position (SEP) municipalities were more likely to be diagnosed with HPV-related cancers and breast cancer than women accessing care in low SEP municipalities. It is important to improve the immunologic status of WLHIV as part of cancer prevention strategies in WLHIV. Cancer prevention and early detection programmes should be tailored to the needs of women ageing with HIV. In addition, SEP disparities in cancer diagnostic services have to be addressed.

Age and Cancer Incidence in 5.2 Million People With Human Immunodeficiency Virus (HIV): The South African HIV Cancer Match Study.

BACKGROUND: Old age is an important risk factor for developing cancer, but few data exist on this association in people with human immunodeficiency virus (HIV, PWH) in sub-Saharan Africa. METHODS: The South African HIV Cancer Match study is a nationwide cohort of PWH based on a linkage between HIV-related laboratory records from the National Health Laboratory Service and cancer diagnoses from the National Cancer Registry for 2004-2014. We included PWH who had HIV-related tests on separate days. Using natural splines, we modeled cancer incidence rates as a function of age. RESULTS: We included 5 222 827 PWH with 29 580 incident cancer diagnoses-most commonly cervical cancer (n = 7418), Kaposi sarcoma (n = 6380), and breast cancer (n = 2748). In young PWH, the incidence rates for infection-related cancers were substantially higher than for infection-unrelated cancers. At age 40 years, the most frequent cancer was cervical cancer in female and Kaposi sarcoma in male PWH. Thereafter, the rates of infection-unrelated cancers increased steeply, particularly among male PWH, where prostate cancer became the most frequent cancer type at older age. Whereas Kaposi sarcoma rates peaked at 34 years (101/100 000 person-years) in male PWH, cervical cancer remained the most frequent cancer among older female PWH. CONCLUSIONS: Infection-related cancers are common in PWH in South Africa, but rates of infection-unrelated cancers overtook those of infection-related cancers after age 54 years in the overall study population. As PWH in South Africa live longer, prevention and early detection of infection-unrelated cancers becomes increasingly important. Meanwhile, control strategies for infection-related cancers, especially cervical cancer, remain essential.

Immunodeficiency and Cancer in 3.5 Million People Living With Human Immunodeficiency Virus (HIV): The South African HIV Cancer Match Study.

BACKGROUND: We analyzed associations between immunodeficiency and cancer incidence in a nationwide cohort of people living with human immunodeficiency virus (HIV; PLWH) in South Africa. METHODS: We used data from the South African HIV Cancer Match Study built on HIV-related laboratory measurements from the National Health Laboratory Services and cancer records from the National Cancer Registry. We evaluated associations between time-updated CD4 cell count and cancer incidence rates using Cox proportional hazards models. We reported adjusted hazard ratios (aHRs) over a grid of CD4 values and estimated the aHR per 100 CD4 cells/µL decrease. RESULTS: Of 3 532 266 PLWH, 15 078 developed cancer. The most common cancers were cervical cancer (4150 cases), Kaposi sarcoma (2262 cases), and non-Hodgkin lymphoma (1060 cases). The association between lower CD4 cell count and higher cancer incidence rates was strongest for conjunctival cancer (aHR per 100 CD4 cells/µL decrease: 1.46; 95% confidence interval [CI], 1.38-1.54), Kaposi sarcoma (aHR, 1.23; 95% CI, 1.20-1.26), and non-Hodgkin lymphoma (aHR, 1.18; 95% CI, 1.14-1.22). Among infection-unrelated cancers, lower CD4 cell counts were associated with higher incidence rates of esophageal cancer (aHR, 1.06; 95% CI, 1.00-1.11) but not breast, lung, or prostate cancer. CONCLUSIONS: Lower CD4 cell counts were associated with an increased risk of developing various infection-related cancers among PLWH. Reducing HIV-induced immunodeficiency may be a potent cancer-prevention strategy among PLWH in sub-Saharan Africa, a region heavily burdened by cancers attributable to infections.

Using text mining techniques to extract prostate cancer predictive information (Gleason score) from semi-structured narrative laboratory reports in the Gauteng province, South Africa.

BACKGROUND: Prostate cancer (PCa) is the leading male neoplasm in South Africa with an age-standardised incidence rate of 68.0 per 100,000 population in 2018. The Gleason score (GS) is the strongest predictive factor for PCa treatment and is embedded within semi-structured prostate biopsy narrative reports. The manual extraction of the GS is labour-intensive. The objective of our study was to explore the use of text mining techniques to automate the extraction of the GS from irregularly reported text-intensive patient reports. METHODS: We used the associated Systematized Nomenclature of Medicine clinical terms morphology and topography codes to identify prostate biopsies with a PCa diagnosis for men aged > 30 years between 2006 and 2016 in the Gauteng Province, South Africa. We developed a text mining algorithm to extract the GS from 1000 biopsy reports with a PCa diagnosis from the National Health Laboratory Service database and validated the algorithm using 1000 biopsies from the private sector. The logical steps for the algorithm were data acquisition, pre-processing, feature extraction, feature value representation, feature selection, information extraction, classification, and discovered knowledge. We evaluated the algorithm using precision, recall and F-score. The GS was manually coded by two experts for both datasets. The top five GS were reported, with the remaining scores categorised as "Other" for both datasets. The percentage of biopsies with a high-risk GS (≥ 8) was also reported. RESULTS: The first output reported an F-score of 0.99 that improved to 1.00 after the algorithm was amended (the GS reported in clinical history was ignored). For the validation dataset, an F-score of 0.99 was reported. The most commonly reported GS were 5 + 4 = 9 (17.6%), 3 + 3 = 6 (17.5%), 4 + 3 = 7 (16.4%), 3 + 4 = 7 (14.7%) and 4 + 4 = 8 (14.2%). For the validation dataset, the most commonly reported GS were: (i) 3 + 3 = 6 (37.7%), (ii) 3 + 4 = 7 (19.4%), (iii) 4 + 3 = 7 (14.9%), (iv) 4 + 4 = 8 (10.0%) and (v) 4 + 5 = 9 (7.4%). A high-risk GS was reported for 31.8% compared to 17.4% for the validation dataset. CONCLUSIONS: We demonstrated reliable extraction of information about GS from narrative text-based patient reports using an in-house developed text mining algorithm. A secondary outcome was that late presentation could be assessed.

Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.

Verbal autopsy (VA) narratives play a crucial role in understanding and documenting the causes of mortality, especially in regions lacking robust medical infrastructure. In this study, we propose a comprehensive approach to extract mortality causes and identify prevalent diseases from VA narratives utilizing advanced text mining techniques, so as to better understand the underlying health issues leading to mortality. Our methodology integrates n-gram-based language processing, Latent Dirichlet Allocation (LDA), and BERTopic, offering a multi-faceted analysis to enhance the accuracy and depth of information extraction. This is a retrospective study that uses secondary data analysis. We used data from the Agincourt Health and Demographic Surveillance Site (HDSS), which had 16338 observations collected between 1993 and 2015. Our text mining steps entailed data acquisition, pre-processing, feature extraction, topic segmentation, and discovered knowledge. The results suggest that the HDSS population may have died from mortality causes such as vomiting, chest/stomach pain, fever, coughing, loss of weight, low energy, headache. Additionally, we discovered that the most prevalent diseases entailed human immunodeficiency virus (HIV), tuberculosis (TB), diarrhoea, cancer, neurological disorders, malaria, diabetes, high blood pressure, chronic ailments (kidney, heart, lung, liver), maternal and accident related deaths. This study is relevant in that it avails valuable insights regarding mortality causes and most prevalent diseases using novel text mining approaches. These results can be integrated in the diagnosis pipeline for ease of human annotation and interpretation. As such, this will help with effective informed intervention programmes that can improve primary health care systems and chronic based delivery, thus increasing life expectancy.

Cancer diagnostic service use in people living with HIV in South Africa: A cross-sectional study.

OBJECTIVE: The objective of this study was to map place of cancer diagnosis in relation to Human Immunodeficiency Virus (HIV) care centre among people living with HIV (PLHIV) within South Africa (SA) using national laboratory database. DESIGN: We linked HIV and cancer laboratory data from 2004-2014 using supervised machine-learning algorithms. We performed a cross-sectional analysis comparing province where individuals accessed their HIV care versus where they had their cancer diagnosis. SETTING: We used laboratory test records related to HIV diagnostics and care, such as CD4 cell counts and percentages, rapid tests, qualitative Polymerase Chain Reaction (PCR), antibody and antigen tests for HIV data that was documented as HIV positive and laboratory diagnosed cancer records from SA. STUDY POPULATION: Our study population consisted of HIV records from the National Health Laboratory Service (NHLS) that linked to cancer record at the National Cancer Registry (NCR) between 2004-2014. PRIMARY AND SECONDARY OUTCOMES: We linked HIV records from NHLS to cancer records at NCR in order to study the inherent characteristics of the population with both HIV and cancer. RESULTS: The study population was 68,284 individuals with cancer and documented HIV related laboratory test. The median age at cancer diagnosis was 40 [IQR, 33-48] years for the study population with most cancers in PLHIV diagnosed in females 70.9% [n = 46,313]. Of all the PLHIV and cancer, 25% (n = 16,364 p < 0.001) sought treatment outside their province of residence with 60.7% (n = 10,235) travelling to Gauteng. KZN had 46.6% (n = 4,107) of its PLHIV getting cancer diagnosis in Gauteng. Western Cape had 95% (n = 6,200) of PLHIV getting cancer diagnosis within the province. CONCLUSIONS: Our results showed health systems inequalities across provinces in SA with respect to cancer diagnosis. KZN for example had nearly half of the PLHIV getting cancer diagnosis outside the province while Western Cape is able to offer cancer diagnostic services to most of the PLHIV in the province. Gauteng is getting over burdened with referral for cancer diagnosis from other provinces. More effort is required to ensure equitable access to cancer diagnostic services within the country.

Decreasing incidence of conjunctival squamous cell carcinoma in people with HIV in South Africa.

BACKGROUND: The main risk factors for squamous cell carcinoma of the conjunctiva (SCCC) are immunodeficiency and exposure to ultraviolet radiation. Little is known about SCCC epidemiology among people with HIV (PWH) in South Africa. METHODS: We used data from the South African HIV Cancer Match study, a nation-wide cohort of PWH in South Africa, created through a privacy-preserving probabilistic record linkage of HIV-related laboratory records from the National Health Laboratory Service and cancer records from the National Cancer Registry from 2004 to 2014. We calculated crude incidence rates, analyzed trends using joinpoint models, and estimated hazard ratios for different risk factors using Royston-Parmar flexible parametric survival models. RESULTS: Among 5 247 968 PWH, 1059 cases of incident SCCC were diagnosed, for a crude overall SCCC incidence rate of 6.8 per 100 000 person-years. The SCCC incidence rate decreased between 2004 and 2014, with an annual percentage change of ‒10.9% (95% confidence interval: ‒13.3 to ‒8.3). PWH residing within latitudes 30°S to 34°S had a 49% lower SCCC risk than those residing at less than 25°S latitude (adjusted hazard ratio = 0.67; 95% confidence interval: 0.55 to 0.82). Other risk factors for SCCC were lower CD4 counts and middle age. There was no evidence for an association of sex or settlement type with SCCC risk. CONCLUSIONS: An increased risk of developing SCCC was associated with lower CD4 counts and residence closer to the equator, indicative of higher ultraviolet radiation exposure. Clinicians and PWH should be educated on known SCCC preventive measures, such as maintaining high CD4 counts and protection from ultraviolet radiation through sunglasses and sunhats when outdoors.

Cancer diagnostic service use in people with HIV in South Africa: a cross-sectional study.

Objective: The objective of this study was to map place of cancer diagnosis in relation to Human Immunodeficiency Virus (HIV) care centre among people with HIV (PWH) within South Africa (SA) using national laboratory database. Design: We linked HIV and cancer laboratory data from 2004-2014 using supervised machine-learning algorithms. We performed a cross-sectional analysis comparing province where individuals accessed their HIV care versus where they had their cancer diagnosis. Setting: We used laboratory test records related to HIV diagnostics and care, such as CD4 cell counts and percentages, rapid tests, qualitative Polymerase Chain Reaction (PCR), antibody and antigen tests for HIV data that was documented as HIV positive and laboratory diagnosed cancer records from SA. Study population: Our study population consisted of HIV records from the National Health Laboratory Service (NHLS) that linked to cancer record at the National Cancer Registry (NCR) between 2004- 2014. Primary and secondary outcomes: We linked HIV records from NHLS to cancer records at NCR in order to study the inherent characteristics of the population with both HIV and cancer. Results: The study population was 68,284 individuals with cancer and documented HIV related laboratory test. The median age at cancer diagnosis was 40 [IQR, 33-48] years for the study population with most cancers in PWH diagnosed in females 70.9% [n=46,313]. Of all the PWH and cancer, 25% (n=16,364 p < 0.001) sought treatment outside their province of residence with 60.7% (n=10,235) travelling to Gauteng. KZN had 46.6% (n=4,107) of its PWH getting cancer diagnosis in Gauteng. Western Cape had 95% (n=6,200) of PWH getting cancer diagnosis within the province. Conclusions: Our results showed health systems inequalities across provinces in South Africa with respect to cancer diagnosis. KZN for example had nearly half of the PWH getting cancer diagnosis outside the province while Western Cape is able to offer cancer diagnostic services to most of the PWH in the province. Gauteng is getting over burdened with referral for cancer diagnosis from other provinces. More effort is required to ensure equitable access to cancer diagnostic services within the country.

Performance evaluation of machine learning and Computer Coded Verbal Autopsy (CCVA) algorithms for cause of death determination: A comparative analysis of data from rural South Africa.

Computer Coded Verbal Autopsy (CCVA) algorithms are commonly used to determine the cause of death (CoD) from questionnaire responses extracted from verbal autopsies (VAs). However, they can only operate on structured data and cannot effectively harness information from unstructured VA narratives. Machine Learning (ML) algorithms have also been applied successfully in determining the CoD from VA narratives, allowing the use of auxiliary information that CCVA algorithms cannot directly utilize. However, most ML-based studies only use responses from the structured questionnaire, and the results lack generalisability and comparability across studies. We present a comparative performance evaluation of ML methods and CCVA algorithms on South African VA narratives data, using data from Agincourt Health and Demographic Surveillance Site (HDSS) with physicians' classifications as the gold standard. The data were collected from 1993 to 2015 and have 16,338 cases. The random forest and extreme gradient boosting classifiers outperformed the other classifiers on the combined dataset, attaining accuracy of 96% respectively, with significant statistical differences in algorithmic performance (p < 0.0001). All our models attained Area Under Receiver Operating Characteristics (AUROC) of greater than 0.884. The InterVA CCVA attained 83% Cause Specific Mortality Fraction accuracy and an Overall Chance-Corrected Concordance of 0.36. We demonstrate that ML models could accurately determine the cause of death from VA narratives. Additionally, through mortality trends and pattern analysis, we discovered that in the first decade of the civil registration system in South Africa, the average life expectancy was approximately 50 years. However, in the second decade, life expectancy significantly dropped, and the population was dying at a much younger average age of 40 years, mostly from the leading HIV related causes. Interestingly, in the third decade, we see a gradual improvement in life expectancy, possibly attributed to effective health intervention programmes. Through a structure and semantic analysis of narratives where experts disagree, we also demonstrate the most frequent terms of traditional healer consultations and visits. The comparative approach also makes this study a baseline that can be used for future research enforcing generalization and comparability. Future study will entail exploring deep learning models for CoD classification.

Cervical cancer in women living in South Africa: a record linkage study of the National Health Laboratory Service and the National Cancer Registry.

INTRODUCTION: In countries with high HIV prevalence, it is important to understand the cervical cancer (CC) patterns by HIV status to ensure targeted prevention measures. We aimed to determine the factors associated with CC compared to non-infection related cancer in women living in South Africa. METHODS: This was a cross-sectional study of women aged 15 years and older diagnosed with CC and non-infection related cancer in the South African public health sector from 2004 to 2014. The National Cancer Registry provided data on cancer, whilst HIV status was determined from routinely collected HIV related data from the National Health Laboratory Service. We explored the association of HIV infection, age, ethnicity and calendar period with CC compared to non-infection related cancer. RESULTS: From 2004 to 2014, 49,599 women were diagnosed with CC, whilst 78,687 women had non-infection related cancer. About 40% (n = 20,063) of those with CC and 28% (n = 5,667) of those with non-infection related cancer had a known HIV status. The median age at CC diagnosis was 44 years (interquartile range (IQR): 37-52) and 54 years (IQR: 46-64) for HIV positive and negative women, respectively, and for non-infection related cancer, 45 years (IQR: 47-55) and 56 years (IQR: 47-66) for HIV negative and positive women, respectively. Diagnosis of CC was associated with HIV positivity, Black ethnicity, earlier calendar period (2004-2006) and the ages 30-49 years. In comparison with Black women, the odds of CC were 44% less in Coloured women, 50% less in Asian women and 51% less in White women. CONCLUSIONS: HIV positive women presented a decade earlier with CC compared to HIV negative women. A large proportion of women with CC were unaware of their HIV status with a disproportionate burden of CC in Black women. We recommend women attending CC screening facilities to be offered HIV testing so that recommendations for their follow-up visits are given according to their HIV status.

Cohort profile: the South African HIV Cancer Match (SAM) Study, a national population-based cohort.

PURPOSE: The South African HIV Cancer Match (SAM) Study is a national cohort of people living with HIV (PLWH). It was created using probabilistic record linkages of routine laboratory records of PLWH retrieved by National Health Laboratory Services (NHLS) and cancer data from the National Cancer Registry. The SAM Study aims to assess the spectrum and risk of cancer in PLWH in the context of the evolving South African HIV epidemic. The SAM Study's overarching goal is to inform cancer prevention and control programmes in PLWH in the era of antiretroviral treatment in South Africa. PARTICIPANTS: PLWH (both adults and children) who accessed HIV care in public sector facilities and had HIV diagnostic or monitoring laboratory tests from NHLS. FINDINGS TO DATE: The SAM cohort currently includes 5 248 648 PLWH for the period 2004 to 2014; 69% of these are women. The median age at cohort entry was 33.0 years (IQR: 26.2-40.9). The overall cancer incidence in males and females was 235.9 (95% CI: 231.5 to 240.5) and 183.7 (181.2-186.2) per 100 000 person-years, respectively.Using data from the SAM Study, we examined national cancer incidence in PLWH and the association of different cancers with immunodeficiency. Cancers with the highest incidence rates were Kaposi sarcoma, cervix, breast, non-Hodgkin's lymphoma and eye cancer. FUTURE PLANS: The SAM Study is a unique, evolving resource for research and surveillance of malignancies in PLWH. The SAM Study will be regularly updated. We plan to enrich the SAM Study through record linkages with other laboratory data within the NHLS (eg, tuberculosis, diabetes and lipid profile data), mortality data and socioeconomic data to facilitate comprehensive epidemiological research of comorbidities among PLWH.

Cancer in HIV-positive and HIV-negative adolescents and young adults in South Africa: a cross-sectional study.

OBJECTIVE: To determine the spectrum of cancers in adolescents and young adults (AYAs) living with and without HIV in South Africa. DESIGN: Cross-sectional study with cancer records provided by the National Cancer Registry (NCR) and HIV records from the National Health Laboratory Service (NHLS). SETTING AND PARTICIPANTS: The NHLS is the largest provider of pathology services in the South African public sector. The NCR is a division of the NHLS. We included AYAs (aged 10-24 years) diagnosed with cancer by public health sector laboratories between 2004 and 2014 (n=8479). HIV status was obtained through record linkages and text mining. PRIMARY AND SECONDARY OUTCOMES: We determined the spectrum of cancers by HIV status in AYAs. We used multivariable logistic regression to describe the association of cancer in AYAs with HIV, adjusting for age, sex, ethnicity and calendar period. We imputed (post hoc) the HIV status for AYA with unknown HIV status. RESULTS: 8479 AYAs were diagnosed with cancer, HIV status was known for 45% (n=3812). Of those whose status was known, about half were HIV positive (n=1853). AYAs living with HIV were more likely to have Kaposi's sarcoma (adjusted OR (aOR) 218, 95% CI 89.9 to 530), cervical cancer (aOR 2.18, 95% CI 1.23 to 3.89), non-Hodgkin's lymphoma (aOR 2.12, 95% CI 1.69 to 2.66) and anogenital cancers other than cervix (aOR 2.73, 95% CI 1.27 to 5.86) than AYAs without HIV. About 44% (n=1062) of AYAs with HIV-related cancers had not been tested for HIV. CONCLUSIONS: Targeted HIV testing for AYAs diagnosed with cancer, followed by immediate start of antiretroviral therapy, screening for cervical precancer and vaccination against human papilloma virus is needed to decrease cancer burden in AYAs living with HIV in South Africa.

Cancer risk in adolescents and young adults living with HIV in South Africa: a nationwide cohort study.

BACKGROUND: Literature on cancer in adolescents and young adults (AYA; aged 15-24 years) living with HIV is scarce. We studied cancer incidence in AYA living with HIV in South Africa between 2004 and 2014. METHODS: In this nationwide cohort study, we included individuals between 15 and 24 years old who had at least two HIV-related laboratory measurements on separate days between Jan 1, 2004, and Dec 31, 2014, recorded in the National Health Laboratory Service database. We used privacy-preserving probabilistic record linkage methods to identify HIV-related laboratory records that most likely belonged to the same individual and to then link these individuals to cancer diagnoses from the National Cancer Registry. We computed incidence rates for the most common cancers in AYA living with HIV, and we assessed associations between these cancers and sex, age, calendar year, and CD4 cell count using Cox proportional hazards models and adjusted hazard ratios (aHRs). FINDINGS: We included 782 454 AYA living with HIV (698 066 [89·2%] women) with 1 428 114 person-years of follow-up. Of those, 867 developed incident cancer (incidence rate 60·7 per 100 000 person-years), including 429 who developed Kaposi sarcoma (30·0 per 100 000 person-years), 107 non-Hodgkin lymphoma (7·5 per 100 000 person-years), 48 Hodgkin lymphoma (3·4 per 100 000 person-years), 45 cervical cancer (3·4 per 100 000 woman-years), and 32 leukaemia (2·2 per 100 000 person-years). Kaposi sarcoma was more common in the 20-24 year age group than the 15-19 year age group (aHR 1·39, 95% CI 1·03-1·86). Male sex was associated with higher rates of Kaposi sarcoma (2·06, 1·61-2·63), non-Hodgkin lymphoma (3·17, 2·06-4·89), Hodgkin lymphoma (4·83, 2·61-8·93), and leukaemia (unadjusted HR 5·90, 95% CI 2·87-12·12). Cancer rates decreased over the study period, driven by declining Kaposi sarcoma rates. Lower baseline CD4 cell counts were associated with higher rates of Kaposi sarcoma, cervical cancer, non-Hodgkin lymphoma, and Hodgkin lymphoma, but not leukaemia. INTERPRETATION: Infection-related cancers were the most common cancer types in AYA living with HIV in South Africa, and their incidence rates increased with lower CD4 cell counts. Therefore, innovative strategies to maintaining high CD4 cell counts are needed to reduce the cancer burden in this vulnerable population. FUNDING: US National Institutes of Health and Swiss National Science Foundation.

The burden of cancers associated with HIV in the South African public health sector, 2004-2014: a record linkage study.

INTRODUCTION: The impact of South Africa's high human immunodeficiency virus (HIV) burden on cancer risk is not fully understood, particularly in the context of antiretroviral treatment (ART) availability. We examined national cancer trends and excess cancer risk in people living with HIV (PLHIV) compared to those who are HIV-negative. METHODS: We used probabilistic record linkage to match cancer records provided by the National Cancer Registry to HIV data provided by the National Health Laboratory Service (NHLS). We also used text search of specific HIV terms from the clinical section of pathology reports to determine HIV status of cancer patients. We used logistic and Joinpoint regression models to evaluate the risk and trends in cancers in PLHIV compared to HIV-negative patients from 2004 to 2014. In sensitivity analysis, we used inverse probability weighting (IPW) to correct for possible selection bias. RESULTS: A total of 329,208 cancer cases from public sector laboratories were reported to the NCR from 2004 to 2014 with the HIV status known for 95,279 (28.9%) cancer cases. About 50% of all the female cancer cases (n = 30,486) with a known status were HIV-positive. PLHIV were at higher risk of AIDS-defining cancers (Kaposi sarcoma [adjusted OR:134, 95% CI:111-162], non-Hodgkin lymphoma [adjusted OR:2.73, 95% CI:2.56-2.91] and, cervix [adjusted OR:1.70, 95% CI:1.63-1.77], conjunctival cancer [adjusted OR:21.5, 95% CI:16.3-28.4] and human papilloma virus (HPV) related cancers (including; penis [adjusted OR:2.35, 95% CI:1.85-2.99], and vulva [adjusted OR:1.94, 95% CI:1.67-2.25]) compared to HIV-negative patients. Analysis using the IPW population yielded comparable results. CONCLUSION: There is need for improved awareness and screening of conjunctival cancer and HPV-associated cancers at HIV care centres. Further research and discussion is warranted on inclusive HPV vaccination in PLHIV.