25 Stereotactic Body Radiation Treatment of Synchronous Early Stage Non-Small Cell Lung Cancers
Bibliographic record
Abstract
CARO-ASM 2019p=0.02).After PCP, SADT was given to significantly more patients in DERT76 (seven, five and 21 patients respectively, p=0.001).Thirteen patients who received intermittent SADT for BF were treated subsequently for PCP.SADT began within six months of BF in 44% of patients, within one year in 65% and within two years in 82%.SADT started later after baseline for patients with ADT+DERT76 than patients with ADT+DERT70 or DERT76 alone (median (range): 70 (31-133), 93 (60-158) and 64 (6-184) months respectively, p=0.051).No statistical difference was observed between ADT+DERT70 and DERT76 alone.There was no significant difference in the total usage of SADT (median (range): 23 (0-107), 9 (0-24) and 9.5 (0-31) months respectively, p=0.25).Of note, 69% (140/202) of all patients treated with RT alone (five in ADT+RT70, four in ADT+DERT76 and 193 in DERT76) did not fail and never received SADT.Conclusions: In IRPC, patients receiving dose-escalated RT alone developed more BF and PCP than those treated with RT combined with neo-adjuvant and concomitant ADT.When ADT was used after BF or PCP, it was mostly timed as an early intervention.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".