Follow-Up Care for Survivors of Lymphoma Who Have Received Curative-Intent Treatment
Bibliographic record
Abstract
Objective: This evidence summary set out to assess the available evidence about the follow-up of asymptomatic survivors of lymphoma who have received curative-intent treatment. Methods: The MEDLINE and EMBASE databases and the Cochrane Database of Systematic Reviews were searched for evidence published between 2000 and August 2015 relating to lymphoma survivorship follow-up. The evidence summary was developed by a Working Group at the request of the Cancer Care Ontario Survivorship and Cancer Imaging programs because of the absence of evidence-based practice documents in Ontario for the follow-up and surveillance of asymptomatic patients with lymphoma in complete remission. Results: Eleven retrospective studies met the inclusion criteria. The proportion of relapses initially detected by clinical manifestations ranged from 13% to 78%; for relapses initially detected by imaging, the proportion ranged from 8% to 46%. Median time for relapse detection ranged from 8.6 to 19 months for patients initially suspected because of imaging and from 8.6 to 33 months for those initially suspected because of clinical manifestations. Only one study reported significantly earlier relapse detection for patients initially suspected because of clinical manifestations (mean: 4.5 months vs. 6.0 months, p = 0.042). No benefit in terms of overall survival was observed for patients depending on whether their relapse was initially detected because of clinical manifestations or surveillance imaging. Findings in the present study support the importance of improving awareness on the part of survivors and clinicians about the symptoms that might be associated with recurrence. The evidence does not support routine imaging for improving outcomes in this patient population.
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 | 0.004 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".