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A Prospective Cost Analysis of Non-Myeloablative Hematopoietic Stem Cell Transplantation.

2005· article· en· W2560062761 on OpenAlexaffabout
Chris Skedgel, Jo-Ann Edwards, Jean Roy, Andrea McNeil, Yvonne Gulliver, Peter Duggan, Darrell White, Stephen Couban

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsMemorial University of NewfoundlandHôpital Maisonneuve-RosemontQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineTransplantationHematopoietic stem cell transplantationEmergency medicineHematopoietic cellActivity-based costingPsychological interventionIndirect costsIntensive care medicineHealth careSurgeryStem cellHaematopoiesisNursing

Abstract

fetched live from OpenAlex

Abstract Hematopoietic stem cell transplantation (HSCT) is an intensive medical therapy used to treat both malignant and non-malignant conditions. Non-myeloablative transplantation (NMT) is an emerging transplant modality often performed on an outpatient basis. While NMT is associated with fewer acute complications compared to myeloablative HSCT, long-term complications, particularly chronic graft vs host disease (GvHD), are of concern. To our knowledge, there have been few economic evaluations of NMT and none in a Canadian healthcare environment. We prospectively developed and validated a process for capturing the costs and outcomes of NMT in order to estimate the cost per patient of NMT at a Canadian transplant centre. Ten consecutive patients undergoing NMT were followed from the first day of conditioning (Day −11) until either 1 year post-transplant or death. Donor costs were also recorded. All patient encounters, procedures and interventions during the study period were prospectively recorded. Nursing and other non-physician human resource costs were calculated based on recorded contact times and salaries. Physician costs were derived from Nova Scotia fee codes. Costs of hospital admissions were derived from Ontario Case Costing Initiative (OCCI) data and were specific to the primary diagnosis. Drug costs were based on acquisition costs at hospital and community pharmacies. Materials and equipment costs were based on costs at the QEII Health Sciences Centre, Halifax NS. The proportion of administrative costs to direct costs was derived from OCCI data and applied to local direct costs. All costs are in 2005 Canadian dollars ($CAN). Ten patients were followed for a median of 12 months (range 3.6–12) from September 2003 to April 2005. Eight patients were male and the median age of the cohort was 60 years (19–73). Five patients had AML; 3 had lymphoma and 2 had multiple myeloma.Cyclophosphamide and fludarabine were used as conditioning and tacrolimus and mycophenolate mofetil were used as GvHD prophylaxis. There were 7 hospital admissions among the 10 patients: 3 before day 100 and 4 after day 100. Eight patients survived at least one year post-transplant. No patients developed acute GvHD, while all 8 patients surviving to 1 year post-transplant developed chronic GvHD. Three patients relapsed within 1 year. The average cost per NMT was $CAN 43,377 of which $CAN 31,761 were recipient costs, $CAN 2,562 were donor costs and $CAN 8,675 were equipment and overhead costs. The key cost driver was hospital admissions for complications and/or palliative care at $CAN 9,793 per recipient. Physician fees ($CAN 6,958) and chemotherapy ($CAN 6,485) were also significant. Compared to published estimates of the cost of myeloablative HSCT, NMT appears considerably less costly in the first year post-transplant. Our analysis suggests that the lower cost of NMT was largely attributable to the limited amount of inpatient care these patients received. Further follow-up will be informative since the major complications of NMT including chronic GvHD and relapse may impact per transplant cost after the first year post-transplant. Direct comparison with myeloablative HSCT using our prospective costing method is also planned.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.962

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.283
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2005
Admission routes2
Has abstractyes

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