The Organization of Clinical Trials for Oncology at IRCCS Istituto Nazionale Tumori “Fondazione G. Pascale” Napoli and the Impact of the OECI Accreditation Process
Bibliographic record
Abstract
The Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale Tumori "Fondazione G. Pascale" (INT-Pascale) is the largest Clinical Care and Research Cancer Center in Southern Italy. The mission is prevention, diagnosis, and care of cancer and innovative research in oncology. In 2013, INT-Pascale joined the Organisation of European Cancer Institutes (OECI) accreditation and classification project along with other Italian IRCCS cancer centers. One of the major OECI requirements that a cancer center must fulfill in order to achieve and maintain OECI certification is a strong emphasis in translational and clinical research: increasing the number of patients enrolled in clinical trials, establishing easily accessible databases for operators, and informing all possible stakeholders, including patients. A characterizing theme of INT-Pascale is a strong commitment to clinical experimental studies. In the 2007-2014 period, 440 clinical trials were activated at INT-Pascale; in this period, the number of clinical trials and observational studies has had an increment achieving in 2014, respectively, the share of 60 clinical trials and 35 observational studies activated. Optimization of clinical trials management and dissemination of the clinical research culture at INT-Pascale are main objectives to be achieved through several actions and procedures being implemented as a component of the OECI improvement plan. Participation in the OECI program has represented an important challenge to improve quality and processes related to promoting, prioritizing, and monitoring clinical trials at INT-Pascale.
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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 | 0.281 | 0.246 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.023 | 0.008 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".