Abstract CT151: A phase II study of optimized individualized adaptive radiation therapy for hepatocellular carcinoma
Bibliographic record
Abstract
Abstract Introduction: Stereotactic body radiation therapy (SBRT) for the treatment of hepatocellular carcinoma (HCC) remains a challenge due to high rates of toxicity in patients with impaired liver function or tumors not amenable to thermal ablation. We performed a single-arm prospective phase II clinical trial utilizing a novel treatment paradigm optimizing the utility of SBRT based on the individual patient’s probability for tumor control traded off against the risk of liver injury. We hypothesized that maximizing the utility of treatment would decrease toxicity while achieving the same tumor control rate as standard therapy. Methods: Patients with Child-Pugh (CP) A to B7 disease with tumors >3.5 cm, or CP ≥ B8 with any size tumor were prospectively enrolled on an IRB approved clinical trial to undergo SBRT with baseline dose optimization and mid-treatment response adaptation. Optimization and adaptation were based on the expected utility of treatment, calculated as a weighted average of the probability of 4 combinations of toxicity and efficacy outcomes. These calculations were based on the individual patient’s baseline indocyanine green retention at 15 minutes or albumin-bilirubin score (ALBI), CP score, intended dose and fractionation, and mean liver dose with the goal of maximizing the difference between the probability of local control compared to the probability of treatment-related toxicity. Primary endpoints were rate of liver decompensation as measured by ≥2 point change in CP score within 6 months, and lesion-specific local control. Overlap weighting was used to compare patients treated on protocol with patients receiving conventional SBRT at another high-volume cancer center. Results: 56 patients with 80 tumors met inclusion criteria and had a median follow-up of 11.2 months. 44 tumors with a median size of 3.8 cm were treated in CP-A to B7 patients, while 36 tumors with a median size of 2.1 cm were treated in CP ≥ B8 patients. Optimization resulted modification of initial dose for 38% of patients. Sixty-eight percent of patients underwent mid-treatment adaptation with either omission or dose reduction of the final two treatments based on change in expected utility. The 1 year freedom from local progression was 94%. A total of 21% of patients experienced a ≥ 2 point change in CP score within 6 months. Overlap weighted analysis revealed similar local control (HR 0.69, 95% CI [0.25-1.91], p = 0.48), and overall survival (HR 1.45, 95% CI [0.69-3.0], p = 0.33), with decreased toxicity (OR 0.26, 95% CI [0.07 - 0.99], p = 0.048) compared to conventional SBRT. Conclusion: SBRT for HCC patients with large tumors or poor liver function can be optimized via an individualized, utility-based treatment paradigm which may decrease treatment-related toxicity while maintaining tumor control. Citation Format: Daniel J. Herr, Chang Wang, Mishal Mendiratta-Lala, Martha Matuszak, Charles S. Mayo, Yue Cao, Neehar Parikh, Randy Ten Hanken, Dawn Owen, Teodor Stanescu, Michael Yan, Laura A. Dawson, Matthew Schipper, Theodore S. Lawrence, Kyle C. Cuneo. A phase II study of optimized individualized adaptive radiation therapy for hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT151.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".