AIDS-Related Malignancies: Emerging Challenges in the Era of Highly Active Antiretroviral Therapy
Bibliographic record
Abstract
Abstract Learning Objectives After completing this course, the reader will be able to: Describe the pathogenesis and clinical presentation of Kaposi's sarcoma, with a special emphasis on Kaposi's sarcoma herpesvirus/human herpesvirus-8, and outline treatment approaches.Discuss the pathogenesis, epidemiology, and treatment of AIDS-related lymphomas.Discuss the increasing incidence of non-AIDS-defining malignancies such as Hodgkin's lymphoma and plasma cell disorders in patients with HIV infection.Explain how, in the era of highly active antiretroviral therapy, both AIDS-related lymphoma and Hodgkin's lymphoma patients may be treated with therapies previously reserved for their immunocompetent counterparts. Access and take the CME test online and receive 1 hour of AMA PRA category 1 credit at CME.TheOncologist.com Human immunodeficiency virus (HIV)-infected patients are at increased risk of developing cancer, particularly in the later stages of acquired immune deficiency syndrome (AIDS). Despite the advent of highly active anti-retroviral therapy (HAART), malignancy in this population is a leading cause of morbidity and mortality. Kaposi's sarcoma (KS) and AIDS-related non-Hodgkin's lymphoma (ARL) are the most common AIDS-defining malignancies. AIDS-related KS varies from minimal to fulminant disease. Treatment decisions for AIDS-related KS are guided largely by the presence and extent of symptomatic disease. In addition to HAART, excellent treatments exist for both localized disease (topical gel, radiotherapy, and intralesional therapy) and advanced disease (liposomal anthracyclines, paclitaxel). Novel therapies that have become available to treat AIDS-related KS include angiogenesis inhibitors and antiviral agents. ARL comprises a heterogeneous group of malignancies. With the immune restoration afforded by HAART, standard-dose chemotherapies now can be safely administered to treat ARL with curative intent. The role of analogous treatments used in HIV-negative patients, including monoclonal antibodies and autologous stem cell transplantation, requires further clarification in HIV-positive patients. HIV-infected patients also appear to be at increased risk for developing certain non-AIDS-defining cancers, such as Hodgkin's lymphoma and multiple myeloma. Although the optimal treatment of these neoplasms is at present uncertain, recent advances in chemotherapy, antiretroviral drugs, and supportive care protocols are allowing for more aggressive management of many of the AIDS-related cancers. This article provides an up-to-date review of the epidemiology, pathogenesis, clinical features, and treatment of various AIDS-related malignancies that are likely to be encountered by an oncologist practicing in the current HAART era.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".