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Adaptive Clinical Neuroblastoma Risk Groups-Tailoring Treatment in Low- and Middle-Income Countries: An International
Wendy B London1, Gabriela Villanueva2, Derek Shyr3
1Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA.
Insights
A new Adaptive Clinical Neuroblastoma Risk Groups (ACNRG) classification uses simple clinical markers to stratify children with neuroblastoma (NB). This approach improves risk assessment and treatment decisions, especially for those in low- and middle-income countries (LMIC).
Area of Science:
- Pediatric Oncology
- Cancer Genomics
- Clinical Biomarkers
Background:
- Neuroblastoma (NB) risk stratification typically requires advanced clinical, histologic, and genomic data.
- Access to these advanced methods is limited in low- and middle-income countries (LMIC).
- There is a critical need for accessible risk stratification tools for NB patients globally.
Purpose of the Study:
- To develop a novel risk/treatment classification for neuroblastoma (NB) applicable in resource-limited settings.
- To create the Adaptive Clinical Neuroblastoma Risk Groups (ACNRG) classification using readily available clinical prognostic biomarkers.
- To address the unmet need for effective NB stratification in LMIC.
Main Methods:
- Survival tree regression analysis was performed on a large dataset (N=14,501) from the International Neuroblastoma Risk Group (INRG) Data Commons.
- Univariate Cox regression models incorporating age, INRG Staging System (INRGSS), lactate dehydrogenase (LDH), and ferritin were used.
- Risk groups were assigned based on treatment assignment and outcomes within terminal nodes, with comparisons to the existing INRG classification.
Main Results:
- Twelve statistically significant pretreatment risk groups were identified, showing varying 5-year event-free survival (EFS) rates.
- The ACNRG classification demonstrated a high concordance rate of 86.6% when compared to the INRG classification.
- Specific risk groups were defined by combinations of INRGSS, age, LDH, and ferritin levels, with distinct prognostic implications.
Conclusions:
- The ACNRG classification is highly prognostic, utilizing easily obtainable clinical markers.
- ACNRG has the potential to significantly improve risk and treatment stratification accuracy for NB patients, particularly in LMIC.
- Prospective validation of the ACNRG classification is planned to further confirm its utility and impact on patient outcomes.
Purpose:
Risk/treatment stratification for children with neuroblastoma (NB) relies on clinical, histologic, and genomic factors. However, most children with cancer live in low- and middle-income countries (LMIC), where access to advanced methods for stratification is limited. To address this unmet need, we developed a novel risk/treatment classification, the Adaptive Clinical Neuroblastoma Risk Groups (ACNRG) using clinical prognostic biomarkers.
Patients And Methods:
A survival tree regression analysis of the International Neuroblastoma Risk Group (INRG) Data Commons (N = 14,501, diagnosed 1990-2014) was performed using univariate Cox regression models (age, International Neuroblastoma Staging System, serum lactate dehydrogenase [LDH], and serum ferritin) of event-free survival (EFS), separately for test and validation sets. Within each terminal node of the survival tree, the proportion of patients by initial treatment assignment and outcome achieved on that treatment were used to subjectively assign risk/treatment intensity (low-, intermediate-, and high-risk). For additional validation, the ACNRG was descriptively compared with INRG classification. Guidelines were developed for determining INRGs Staging System (INRGSS) in LMIC, using the minimum essential versus optimal imaging/biopsy procedures.
Results:
Twelve statistically, clinically significant unique pretreatment risk groups of INRGSS/age/LDH/ferritin were identified (5-year EFS): low-L1/any/any/any (92% ± 0.5%); intermediate-L2/<18 months/<1,400/any (88% ± 1%), MS/any/<1,400/any (86% ± 1.5%), M/<12 months/<1,400/any (76% ± 2.3%); intermediate/high-L2/<18 months/≥1,400/any (73% ± 4.7%), L2/≥18 months/<1,400/<30 (68% ± 3.4%), L2/≥18 months/<1,400/≥30 (59% ± 3.7%), MS/any/≥1,400/any (52% ± 6.3%); high-L2/≥18 months/≥1,400/any (46% ± 4.7%), M/12-18 months/<1,400/any (64% ± 4.1%), M/<18 months/≥1,400/any (60% ± 1.6%), M/≥18 months/any/any (28% ± 0.8%). The concordance and discordance rates of ACNRG versus INRG were 86.6% and 13.4%, respectively (n = 8,152 nonmissing-data intersection).
Conclusion:
The ACNRG classification, using easily obtained clinical markers, is highly prognostic. The ACNRG could transform risk and treatment stratification, improve accuracy of treatment intensity decisions, and potentially improve outcome, for the large number of children with NB in LMIC. Prospective validation of the ACNRG classification is planned in a pilot trial.
