The role of 2‐deoxy‐2‐[F‐18]fluoro‐D‐glucose positron emission tomography in disseminated carcinoma of unknown primary site
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Bibliographic record
Abstract
BACKGROUND: The authors conducted a comprehensive review of the efficacy of 2-deoxy-2-[F-18]fluoro-D-glucose positron emission tomography (FDG-PET) in the detection of primary tumors in patients with disseminated carcinoma of unknown primary site. METHODS: Ten studies (involving a total of 221 patients) tat were published between 1998 and 2006 were reviewed. Each study evaluated the role of FDG-PET in the detection of unknown primary tumors after a conventional diagnostic workup. Although 94% of patients had a single site of metastases, the studies otherwise were very heterogeneous in the studied population, study design, and additional diagnostic workup. RESULTS: In 41% of patients, FDG-PET detected primary tumors that were not apparent after conventional workup. In this group of patients, the overall sensitivity, specificity, and accuracy rates of FDG-PET in detecting unknown primary tumors were 91.9%, 81.9%, and 80.5%, respectively. FDG-PET imaging also led to the detection of previously unrecognized metastases in 37% of patients. Lung cancers represented 59% of the detected tumors. FDG-PET had a notably high false-positive rate (58.3%) in tumors of the lower digestive tract. FDG-PET altered the clinical management in 34.7% of patients. Most of those patients (53%) received specific chemotherapy for lung and pancreatic cancers; whereas 12% received specific therapy for breast, ovarian, and prostate cancers; and 14% underwent surgery with curative intent. CONCLUSIONS: FDG-PET was an efficient method for detecting primary tumors that were undetected by other modalities and was sensitive for the detection of previously unrecognized metastases. FDG-PET significantly changed clinical management in approximately one-third of the patients studied.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it