“If I am here, it is because the system failed”: a critical qualitative study of global commercial clinical trials for advanced cancer in Chile
Bibliographic record
Abstract
BACKGROUND: The pharmaceutical industry is a key global health actor given its crucial role in the development and testing of medicines. Within Latin America, Chile currently has the highest number of multinational commercial clinical trials per inhabitant, predominantly for oncological therapies. Insufficient attention has been paid to context-specific conditions that enable clinical trials' successful implementation in the Global South. In examining what makes Chile an attractive hub for commercial trials and why patients enroll in them, this study seeks to elucidate the interplay among the pharmaceutical industry, health systems, and societies. We analyze how trial providers, cancer practitioners, and patient participants draw from their own lived experience to make sense of local healthcare, health policies and global pharmaceutical market trends, amid global health crises. METHODS: Using a critical political economy of global health framework, we conducted a critical ethnography in 2022-23 at a tertiary cancer center that is the lead recruiter of patients into oncology commercial trials in Santiago, Chile. In-depth interviews, participant observation, and document gathering were conducted, with materials analyzed through thematic content analysis using Nvivo12. RESULTS: Forty-seven subjects -fourteen patients, four caregivers, and twenty-nine providers- were interviewed and/or shadowed. The main theme, "A failed (health) system" reveals a perception that the growing presence of commercial clinical trials for advanced cancer works synergistically with a deficient health system. Subthemes of political economy levels of (mal)functioning, were grouped as follows: (i) the COVID-19 pandemic and the global organization of commercial trials; (ii) national factors (health services and post-trial access policies); and (iii) community/relational factors (palliative care and unaffordability of high-cost drugs). Clinical trials were experienced as an exit strategy from a broken healthcare system, even as participants regarded the pricing strategies of anticancer therapies acritically. CONCLUSIONS: The conditions that make Chile an attractive hub for cancer commercial clinical trials are determined by an interplay of global, national, and community-level structural arrangements between public and private actors. Chile serves as an important global health case study on the role of the pharmaceutical industry in capitalizing on systemic healthcare failures to advance clinical research on metastatic cancer.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".