Current Status and Future Perspectives of Immunotherapy in Middle-Income Countries: A Single-Center Early Experience
Bibliographic record
Abstract
BACKGROUND: Immunotherapy agents offer novel treatment options in advanced cancers. However, their use is limited in developing countries lacking unifying guidelines and can be followed by a financial burden. In this study, we aimed to provide an overview regarding the use of immunotherapy and the overall response to treatment in patients with metastatic disease in relation to cost-effectiveness. METHODS: This was a retrospective study involving adult metastatic cancer patients, treated with programmed cell death-1 (PD-1) inhibitors at American University of Beirut Medical Center (AUBMC), a tertiary cancer center in Lebanon. Study enrollment began on January 1, 2014 and ended on January 12, 2016. Baseline demographics, epidemiological and clinical data were collected from the patients' records. RESULTS: Our study consisted of 34 patients. Fifteen patients self-financed the treatment. The patients were prescribed immunotherapy without programmed cell death-ligand 1 (PD-L1) testing as it was not part of the guidelines at the time. Twenty-two patients were treated with nivolumab and 12 patients with pembrolizumab. Thirteen patients showed partial response or stable disease, while 21 patients showed progression. CONCLUSION: Improvement in terms of overall survival and progression-free survival has been undercut by the lack of availability of these drugs and their cost. Considering that a large percentage of patients do not respond to immunotherapy, there is a need to use guidelines such as a preset PD-L1 level that ensure cost-effectiveness and prevent resource waste.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".