Stereotactic body radiotherapy (SBRT) and medical inoperability of early stage non-small cell lung cancer
Bibliographic record
Abstract
17074 Background: Early stage NSCLC is commonly diagnosed in elderly patients who often have significant medical co-morbidity. SBRT is emerging as a treatment alternative that can provide 80–97% local control for peripheral tumors. We performed a literature review and a retrospective review of 24 patients referred to Princess Margaret Hospital for consideration of SBRT to assess what criteria were used to determine patient selection for this new treatment. Methods: Published papers reporting treating stage I NSCLC with SBRT were reviewed. Clinical and demographic characteristics of patients referred for consideration of SBRT over the last 15 months were analyzed. All patients were assessed by experienced thoracic surgeons to determine their operability status. Patients were retrospectively scored as average or high risk for surgery on the basis of accepted PFT guidelines (FEV1 and DLCO <40% predicted); Charlson Index of Comorbidity (CCI) was calculated (score >2 associated with impaired survival). Results: Of 13 papers reporting Stage 1 SBRT results, 8 included details of medical inoperability. 2 papers had strict guidelines for PFTs, in addition to other criteria. In 6 studies reporting 276 pts, the most common reason for inoperability was non-specific medical comorbidity (60%). Our cohort (24 patients) referred for SBRT (median age 75, range 57–89) had a mean tumour size of 2.32cm (S.D. 1.11); 50% of patients had a good (0–1) Zubrod Performance status. Based upon PFT tests alone 10 patients (42%) were high risk and 5 (21%) average risk for surgery. The CCI score was ≥3 in 10 patients (42%). 3 patients who scored average risk and CCI ≤2 were deemed medically inoperable due a single severe medical comorbity. In 23/24 pts the surgeon recommended against surgery; one patient refused surgery. Conclusions: With an aging population and increased detection due to incidental finding or screening, it is important to know that there is effective alternative therapy for patients deemed too high risk for surgical resection. Comorbidity is an important factor influencing surgical mortality; defining explicit criteria for inoperability remains a clinical challenge. No significant financial relationships to disclose.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".