Abstract 818P
Background
Acute myeloid leukemia (AML) is a low-volume, high-risk malignancy that requires complex treatment strategies, notably intensive remission induction chemotherapy (ICT) administered to eligible patients based on specific clinical and disease-related characteristics. However, ICT treatment harbors the risk of life-threatening complications. Given the potential benefits of increased practice, high-volume hospitals might be more adept in managing AML. To create understanding in the volume-outcome relationship in AML care, we conducted a nationwide, population-based study in the Netherlands to assess the association between hospital volume and patient outcomes in ICT-treated adult patients with AML.
Methods
We used data from the Netherlands Cancer Registry (NCR), including all adults (≥18 years) diagnosed with AML between January 1, 2014, and December 31, 2018. The association between hospital volume and overall survival (OS) was assessed using mixed effects Cox regression, adjusting for patient and disease characteristics (i.e., case-mix), with hospital as a random effect. We examined the association between hospital volume at different time points after ICT initiation, namely 30-day OS (i.e., after one ICT cycle), 42-day OS (i.e., after two cycles of ICT), and 100-day OS (i.e., after SCT).
Results
A total of, 4,060 adults (≥18 years) were diagnosed with AML in the Netherlands, of which 1,761 (43%) received ICT in 24 hospitals. Hospital volume per year ranged from 1 to 56 patients, with a median of 13 patients (IQR, 8-20 patients). Overall, an increase of 10 ICT-treated patients annually was associated with a 8% reduction in mortality risk (hazard ratio, 0.92; 95% confidence interval, 0.87-0.98; P=0.01). This association was not significant at 30 and 42 days OS but became apparent after 100 days OS.
Conclusions
Our study shows that there is no association between hospital volume and short-term outcomes, but with longer-term outcomes, in ICT-treated adult patients with AML. While our findings support hospital volume as a metric in AML care, any policy shifts towards centralization based on volume must be carefully balanced, considering potential drawbacks and prioritizing patient welfare and the healthcare system.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1192P - Optimizing lung cancer screening: Independent verification of an AI/ML computer-aided detection and characterization software as medical device
Presenter: Sylvain Bodard
Session: Poster session 09
1194P - Development of a novel artificial intelligence (AI) algorithm to detect pulmonary nodules on chest radiography
Presenter: Mitsunori Higuchi
Session: Poster session 09
1195P - Whole-body magnetic resonance imaging (WB-MRI) screening in Li Fraumeni syndrome for early cancer diagnosis: The SIGNIFIED project
Presenter: Elena Cojocaru
Session: Poster session 09
1196P - Organoid growth-based oncological sensitivity test (OncoSensi) for predicting adjuvant therapy outcomes in ovarian cancer patients
Presenter: Dong Woo Lee
Session: Poster session 09
1197P - Ex vivo basket study reports patient-specific sensitivity to carboplatin versus cisplatin in lung, ovarian and bladder cancer
Presenter: Debbie Robbrecht
Session: Poster session 09
1198P - Analytical validation of an NGS panel-based ecDNA detection device for use as a clinical trial assay for the POTENTIATE clinical study of the novel CHK1 inhibitor, BBI-355
Presenter: Pontis Julien
Session: Poster session 09