Clinical utility of interim CT scans in patients receiving chemoimmuntherapy for first line treatment of follicular lymphoma
Bibliographic record
Abstract
Interim imaging with computed tomography (iCT) to assess response is common during frontline chemoimmunotherapy for follicular lymphoma (FL), but there is little evidence of its utility. We retrospectively reviewed outcomes of iCT in 190 patients with biopsy-proven FL who received first-line chemoimmunotherapy from 2003-2018. Most iCTs showed partial response (PR, 83%), with a minority showing complete response (CR, 8%) or stable disease (5%). Seven patients (4%) had radiographic disease progression (PD) on iCT; on repeat biopsy, four had another malignancy identified and three had transformation to DLBCL. Only one had asymptomatic PD. The 3-year PFS of all patients was 74% (median follow up 75 months). Patients with PR on iCT had similar 3-year PFS and OS as those with CR. In conclusion, iCT has limited utility in identifying patients with asymptomatic early progression during first-line treatment. Patients with PD mid-treatment warrant biopsy to identify histologic transformation or other malignancies.
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 | 0.005 |
| 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 | 0.001 | 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".