Utility of positron emission tomography (PET) scans on the management of cancers of unknown primary.
Bibliographic record
Abstract
6066 Background: PET scans can be potentially useful in the diagnostic and staging workup of certain cancers. Although frequently ordered, its precise role in the investigation and management of cancers of unknown primary (CUP) remains poorly defined. Our main study aims were to 1) compare the utility of PET vs. CT scans in determining the primary site, lymph node status, and metastases for patients with CUP, and 2) describe the overall survival of patients for whom the primary site was determined by PET vs. those who were not. Methods: Patients diagnosed with CUP in British Columbia, Canada from 2006 to 2009, evaluated at 1 of 5 regional cancer centers in the province, and underwent a PET scan were reviewed. We measured concordance rates between PET and CT scans and constructed regression models to characterize the effect of PET scans on treatment and survival. Results: A total of 175 patients were included: median age was 60 years and 76% were men. PET scans were most commonly performed for the following indications: locating primary (45%); staging (42%); and others (13%). Among those in whom CT did not detect the primary site, PET revealed the location of the primary in 9% of cases. CTs and PETs were concordant in demonstrating nodal status and metastases in 91% and 95% of patients, respectively. PET scans were able to show additional nodal involvement and uncover metastatic disease in 9% and 5%, respectively, when compared to CT scans. Identification of the site of primary cancer by PET did not substantially modify subsequent therapy (p=0.37) and it also failed to significantly improve the median overall survival (10.1 vs. 7.3 months, p=0.57) when compared to those in whom the location of the primary was unconfirmed. Conclusions: In this retrospective cohort of CUP patients, CT and PET scans appear to provide a similar level of diagnostic and staging information. For a small proportion of CUP patients, PETs were superior in clarifying the primary site, nodal status, and metastases, but these did not alter therapy or increase overall survival. Based on these findings and considering the cost implications of intensive imaging studies, the diagnostic value of PET scans over CT scans appears limited to a small subset of patients with CUP.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".