Use of positron emission tomography-computed tomography (PET-CT) scan in patients with gastrointestinal (GI) cancer at the University Hospital of Montreal (CHUM).
Bibliographic record
Abstract
793 Background: In the province of Quebec, Canada, PET-CT scan recommendations are published by the Institut national d’excellence en santé et en services sociaux (INESSS). These recommendations are based on evidence-based literature and publications from oncology societies (ASCO, NCCN...) Judicious use of PET-CT scans is particularly important in a public health system for appropriate allocation of resources. An analysis conducted by INESSS in 2017 demonstrated a remarkable use of 507 PET-CT scans per 100,000 persons in Quebec, an incidence more than twice as high as other provinces, and equivalent to that of the United States (510 per 100,000 person). Methods: We present a retrospective quality control study in which all PET-CT scans completed for oncologic purposes for patients of 18 years or older at CHUM between September 1st and November 30th, 2019, were included. Patients who had a PET-CT scan for non-oncologic purposes or weren’t followed at the CHUM were excluded. We reviewed disease characteristics of patients, and adherence to 2017 INESSS guidelines. All cancer types were analysed and classified according to imaging reason (staging, response to treatment, follow up). We herein report the use of PET-CT in GI cancers and how it compares to INESSS recommendation . Results: A total of 2331 PET-CT scans were completed in the studied period. Among them 975 PET-CT scans fit our inclusion criteria. 155 patients (16%) underwent PET-CT scans for GI cancers. Only 35% followed INESSS recommendations, 44% did not, and 21% had GI cancer types without revised clear recommendations from INESSS. Among specialists, surgeons requested most PET-CT scans (66%), but surgeons, oncologists, and gastroenterologist were equally non-adherent to guidelines (44, 45, and 43% respectively). Strikingly, 43% of PET-CT scans for GI cancers were prescribed for cancer follow up, yet 83% did not follow guidelines. Most PET-CT scans were used for colorectal (41%) or gastroesophageal cancers (28%), and only 40 and 53% followed guidelines, respectively. 49.7% of PET-CT scans did not result in treatment modification. Conclusions: In our university hospital, more than 40% of PET-CT scans prescribed don’t follow INESSS recommendations. In the interest of proper resource allocation in a public health care system, we recommend guideline adherence and discussion in multidisciplinary Tumour Boards prior to off-label use of PET-CT scans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".