Predictors of Financial Toxicity in Patients Receiving Concurrent Radiation Therapy and Chemotherapy.

Purpose: Financial toxicity (FT) is a significant concern for patients with cancer. We reviewed prospectively collected data to explore associations with FT among patients undergoing concurrent, definitive chemoradiation therapy (CRT) within a diverse, urban, academic radiation oncology department. Methods and Materials: Patients received CRT in 1 of 3 prospective trials. FT was evaluated before CRT (baseline) and then weekly using the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire Core-30 questionnaire. Patients were classified as experiencing FT if they answered ≥2 on a Likert scale question (1-4 points) asking if they experienced FT. Rate of change of FT was calculated using linear regression; worsening FT was defined as increase ≥1 point per month. χ2, t tests, and logistic regression were used to assess predictors of FT. Results: Among 233 patients, patients attended an average of 9 outpatient and 4 radiology appointments over the 47 days between diagnosis and starting CRT. At baseline, 52% of patients reported experiencing FT. Advanced T stage (odds ratio, 2.47; P = .002) was associated with baseline FT in multivariate analysis. The mean rate of FT change was 0.23 Likert scale points per month. In total, 26% of patients demonstrated worsening FT during CRT. FT at baseline was not associated with worsening FT (P = .98). Hospitalization during treatment was associated with worsening FT (odds ratio, 2.30; P = .019) in multivariate analysis. Conclusions: Most patients reported FT before CRT. These results suggest that FT should be assessed (and, potentially, addressed) before starting definitive treatment because it develops early in a patient's cancer journey. Reducing hospitalizations may mitigate worsening FT. Further research is warranted to design interventions to reduce FT and avoid hospitalizations.

Improving Adjuvant Liver-Directed Treatment Recommendations for Unresectable Hepatocellular Carcinoma: An Artificial Intelligence-Based Decision-Making Tool.

PURPOSE: Liver-directed therapy after transarterial chemoembolization (TACE) can lead to improvement in survival for selected patients with unresectable hepatocellular carcinoma (HCC). However, there is uncertainty in the appropriate application and modality of therapy in current clinical practice guidelines. The aim of this study was to develop a proof-of-concept, machine learning (ML) model for treatment recommendation in patients previously treated with TACE and select patients who might benefit from additional treatment with combination stereotactic body radiotherapy (SBRT) or radiofrequency ablation (RFA). METHODS: This retrospective observational study was based on data from an urban, academic hospital system selecting for patients diagnosed with stage I-III HCC from January 1, 2008, to December 31, 2018, treated with TACE, followed by adjuvant RFA, SBRT, or no additional liver-directed modality. A feedforward, ML ensemble model provided a treatment recommendation on the basis of pairwise assessments evaluating each potential treatment option and estimated benefit in survival. RESULTS: Two hundred thirty-seven patients met inclusion criteria, of whom 54 (23%) and 49 (21%) received combination of TACE and SBRT or TACE and RFA, respectively. The ML model suggested a different consolidative modality in 32.7% of cases among patients who had previously received combination treatment. Patients treated in concordance with model recommendations had significant improvement in progression-free survival (hazard ratio 0.5; P = .007). The most important features for model prediction were cause of cirrhosis, stage of disease, and albumin-bilirubin grade (a measure of liver function). CONCLUSION: In this proof-of-concept study, an ensemble ML model was able to provide treatment recommendations for HCC who had undergone prior TACE. Additional treatment in line with model recommendations was associated with significant improvement in progression-free survival, suggesting a potential benefit for ML-guided medical decision making.

Centers with more therapeutic modalities are associated with improved outcomes for patients with hepatocellular carcinoma.

BACKGROUND: Higher facility volume is correlated to better overall survival (OS), but there is little knowledge on the effect of facility treatment modality number on OS in hepatocellular carcinoma (HCC). METHODS: This is a retrospective analysis of data from the National Cancer Database (NCDB) from 2004-2014 on patients with non-metastatic HCC. Treatment modalities assessed were surgical resection, transplantation, ablation, radioembolization, stereotactic body radiation therapy (SBRT), single-agent chemotherapy, and multi-agent chemotherapy. Facilities were dichotomized at the median of the listed treatment modalities. RESULTS: There were a total of 112,512 patients with non-metastatic HCC. Of a total of 1,230 sites, 830 (67.5%) used four or fewer modalities. Average survival for patients treated at facilities using fewer modalities was 12.0 and 23.5 months for those treated at facilities with more modalities [hazard ratio (HR) =0.52, 95% confidence interval (CI): 0.51-0.53, P<0.001]. After adjusting for facility volume, liver function, tumor and patient characteristics and other prognostic factors in a multivariable Cox model, treatment at a multi-modality facility still provided a survival advantage (HR =0.60, 95% CI: 0.52-0.70, P<0.001). This benefit also persisted after propensity score matching. Sensitivity analysis varying the cut point from 2 to 6 modalities for dichotomization showed that the benefit persisted. Subgroup stratified analyses based on stage showed that the benefit in OS was highest for patients with stage I and II (P≤0.002) but was not significant for stage III or IVa. CONCLUSIONS: Institutions that offered more treatment modalities had improved OS for patients with non-metastatic HCC, especially for those with stage I and II.