Quantifying the Burden of Cancer in People Living with HIV in Ontario and Examining Associations between CD4 Measures and Cancer Risk
Bibliographic record
Abstract
Cancer is an important co-morbidity for people with human immunodeficiency virus (HIV). People with HIV are at greater risk of certain cancers than people without HIV. In this dissertation, I present three novel studies examining the epidemiology of cancer in adults living with HIV in Ontario. The first manuscript aimed to examine trends in cancer incidence between 1997 and 2020 and to estimate cancer prevalence in people with HIV in Ontario and found that the incidence of any cancer among people with HIV decreased from 1997-2000 to 2016-2020, largely driven by a considerable decrease in the incidence of AIDS-defining cancers. The second manuscript aimed to compare trends in the incidence of infection-related cancers and infection-unrelated cancers among people with HIV and without HIV in Ontario from 1996 to 2020. People with HIV had similar hazard rates of infection-unrelated cancer but increased hazard rates of infection-related cancer, particularly in younger age groups. The cumulative risk of infection-related cancers by age 65 and 75 for people with HIV decreased over time but remained higher than people without HIV of the same age. The third manuscript aimed to examine associations between CD4 measures and infection-related and -unrelated cancer. Low CD4 indicators were associated with an increased rate of infection-related cancer when compared to optimal indicators. In summary, this body of work increased and advanced knowledge, as well as raised awareness of the burden of cancer among people with HIV as an important comorbidity. Understanding the burden of cancer and cancer risk among people living with HIV is foundational to informing and evaluating primary and secondary cancer prevention activities. Evidence from the third study indicated that early diagnosis and linkage to care, as well as early antiretroviral therapy uptake, may lead to improved immune function, as indicated by higher CD4 indices, and could be essential as a cancer prevention strategy for people living with HIV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".