Postsurgical treatment landscape and economic burden of locoregional and distant recurrence in patients with operable nonmetastatic melanoma
Bibliographic record
Abstract
Surgery is the mainstay treatment for operable nonmetastatic melanoma, but recurrences are common and limit patients' survival. This study aimed to describe real-world patterns of treatment and recurrence in patients with melanoma and to quantify healthcare resource utilization (HRU) and costs associated with episodes of locoregional/distant recurrences. Adults with nonmetastatic melanoma who underwent melanoma lymph node surgery were identified from the Truven Health MarketScan database (1 January 2008 to 31 July 2017). Locoregional and distant recurrence(s) were identified on the basis of postsurgery recurrence indicators (i.e. initiation of new melanoma pharmacotherapy, new radiotherapy, or new surgery; secondary malignancy diagnoses). Of 6400 eligible patients, 219 (3.4%) initiated adjuvant therapy within 3 months of surgery, mostly with interferon α-2b (n=206/219, 94.1%). A total of 1191/6400 (18.6%) patients developed recurrence(s) over a median follow-up of 23.1 months (102/6400, 1.6% distant recurrences). Among the 219 patients initiated on adjuvant therapy, 73 (33.3%) experienced recurrences (distant recurrences: 13/219, 5.9%). The mean total all-cause healthcare cost was $2645 per patient per month (PPPM) during locoregional recurrence episodes and $12 940 PPPM during distant recurrence episodes. In the year after recurrence, HRU was particularly higher in patients with distant recurrence versus recurrence-free matched controls: by 9.2 inpatient admissions, 54.4 inpatient days, 8.8 emergency department admissions, and 185.9 outpatient visits (per 100 person-months), whereas all-cause healthcare costs were higher by $14 953 PPPM. It remains to be determined whether the new generation of adjuvant therapies, such as immune checkpoint inhibitors and targeted agents, will increase the use of adjuvant therapies, and reduce the risk of recurrences and associated HRU/cost.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".