High-dose chemotherapy and autologous stem cell transplantation of patients with multiple myeloma in an outpatient setting
Bibliographic record
Abstract
BACKGROUND: High-dose (HD) chemotherapy with melphalan and autologous blood stem cell transplantation (ABSCT) for treatment of symptomatic multiple myeloma (MM) on an outpatient basis has been well established in the USA and Canada, whereas in Germany and Western Europe an inpatient setting is the current standard. We report on a German single-centre program to offer the procedure on an outpatient basis to selected patients. METHODS: Major requirements included: patients had to have family and/or other caregivers, had to be able to reach the hospital within 45 min and have an ECOG performance score of 0-1. Patients with severe co-morbidities were not included. RESULTS: From September 2012 until April 2016, 21 patients with MM stage IIIA were enrolled. All engrafted within the expected time range (median 14 days), and no severe adverse events occurred. 14 patients (67%) had an episode of neutropenic fever and blood cultures were positive in 4 patients (19%). Although rather liberal criteria for hospital admission were applied, 14 patients (67%) were treated entirely on an outpatient basis. CONCLUSIONS: HD chemotherapy and ABSCT on an outpatient basis is safe and feasible if it is conducted in an elaborate surveillance program. The feedback from patients was very positive, thus encouraging further expansion of the program.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".