Assessment of Value Using the American Society of Clinical Oncology (ASCO) and European Society of Medical Oncology (ESMO) Frameworks for Novel Therapies for the Hematologic Malignancies
Bibliographic record
Abstract
Abstract Introduction The cost of cancer care is rising to unsustainable levels, predominantly driven by an increase in expenditures for novel therapies. In the era of biologic therapies, these excessive costs are disproportionately borne by patients with hematologic malignancies. Although the American Society of Clinical Oncology (ASCO) and European Society of Medical Oncology (ESMO) have both developed frameworks to determine the relative value associated with new solid tumor therapies (and specifically with ESMO, to the exclusion of therapies in hematology), it is unclear if they can be applied in the assessment of value of treatments for blood cancers. Methods We evaluated the value of new therapies for hematologic malignancies using the ASCO (version 1 from August 10, 2015 and version 2 from May 31, 2016) and ESMO (version 1 or v1) frameworks. All US Food and Drug Administration, European Medicinal Agency, or Health Canada approved parenteral therapies for hematologic malignancies from 2006-2015 were identified. A systematic review of randomized controlled trials (RCTs) for these therapies was conducted. Two reviewers independently scored the trials using the ASCO value framework v1 (range of scores -20 to 130), v2 (lower range undefined to 180) and ESMO Magnitude of Clinical Benefit Scale (range 1-5). Disagreements were descriptively presented and resolved by consensus. The concurrent validity between the ASCO and ESMO scores was measured by the Spearman correlation coefficient. Results Twenty-three RCTs in malignant hematology were identified and scored. Seven of 23 studies reported primary outcomes unique to hematologic malignancies (for example, time-to-progression in myeloma, cytogenetic response in chronic myeloid leukemia, and symptomatic response in multicentric Castleman's), other than the main outcomes used to derive ASCO/ESMO scores (overall and progression-free survival). The median ASCO v1 score for the trials was 24 (IQR 22-40, min 6 and max 53). The median ASCO v2 score was 26.7 (IQR 17.4-37.6, min -33.3 and max 116.3). The median ESMO score was 2 (IQR 2-3, min 1 and max 4). Using the ASCO v1 framework, 10 studies resulted in disagreements in scoring, predominantly due to variable interpretations of the scoring system. Two studies could not be scored. One study did not report toxicity grades and another study of maintenance rituximab in lymphoma did not report on conventional oncology outcomes that could fit into the ASCO model. Using the ASCO v2 framework, 14 studies resulted in disagreements, predominantly due to differences in scoring toxicities. With the ESMO Scale, 12 studies resulted in disagreements, most occurring due to variable interpretations in scoring survival or progression-free survival outcomes when median values were not provided in the study publication. Two studies could not be scored with the ESMO Scale. One study did not report hazard ratios and another study's reported outcomes did not fit the ESMO scoring options. The correlation coefficient between ASCO v1 and ESMO scores was 0.10 (95% CI: -0.37 to 0.53), suggesting that the correlation was not significantly different from chance only. The coefficient between ASCO v2 and ESMO was -0.21 (95% CI: -0.59 to 0.24) and between ASCO v1 and ASCO v2 was 0.30 (95% CI: -0.15 to 0.65). Conclusions Current value frameworks are challenging to apply to therapies for hematologic malignancies. When studies could be scored, the correlations between ASCO (v1 and v2) and ESMO results were poor, suggesting that these frameworks may not reliably identify the value of therapies in hematology. Consideration for the unique outcomes and toxicities in this population is warranted. The ASCO and ESMO frameworks continue to evolve, and a partnership with societies representing hematologists and their patients would be fruitful. Disclosures No relevant conflicts of interest to declare.
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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 | 0.231 | 0.457 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.046 | 0.037 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".