Highlights of FDA Oncology Approvals in 2023: Bispecific T-cell Engagers, Pediatric Indications, and Inclusive Drug Development.

SUMMARY: Cancer drug development remained robust in 2023. Highlights of U.S. drug approvals this year include new immunotherapies and targeted drug development in adult and pediatric patients as well as patients with rare diseases.

Clinicopathologic predictors of outcomes in children with stage I testicular germ cell tumors: A pooled post hoc analysis of trials from the Children's Oncology Group.

BACKGROUND: Patients with clinical stage I (CS I: cN0M0) testicular germ cell tumors (TGCT) exhibit favorable oncologic outcomes. While prognostic features can help inform treatment in adults with CS I TGCT, we lack reliable means to predict relapse among pediatric and adolescent patients. OBJECTIVE: We sought to identify predictors of relapse in children with CS I TGCT. STUDY DESIGN: We performed a pooled post hoc analysis on pediatric and adolescent AJCC CS I TGCT patients enrolled in 3 prospective trials: INT-0097 (phase II), INT-0106 (phase III), and AGCT0132 (phase III). Pathology was centrally reviewed. Patient demographics, pT stage, serum tumor markers, margin status, histology, relapse, and survival were compiled. Cox regression analyses were used to identify predictors of events, defined as relapse, secondary malignant neoplasm, or death. RESULTS: 106 patients were identified with outcomes data available. Most patients were pT1-2 stage. Among patients with evaluable histopathology, yolk sac tumor elements were present in all patients and lymphovascular invasion in 51% of patients. Over a median follow-up of 56 months, no patients died, and 25 patients (24%) experienced an event (median event-free survival not reached). Independent predictors of events on multivariable analysis included age ≥12 years at diagnosis (HR 8.87, p < 0.001) and higher pT stage (pT2 HR 7.31, p = 0.0017; pT3 HR 13.5, p = 0.0043). DISCUSSION: Although our study population reflects the largest pooled prospective cohort of CS I pediatric and adolescent TGCT to our knowledge, the relatively low event rate limits our multivariable analysis, and longer follow-up duration would help further characterize the natural history of these patients. Centralized pathologic review was also unable to be performed for several patients. CONCLUSION: Pediatric and adolescent CS I TGCT patients exhibit remarkable 5-year survival. Using combined data from multiple prospective trials, our study identifies clinicopathologic features that predict relapse and inform personalized treatment for these patients by potentially guiding surveillance versus adjuvant treatment strategies.

Harnessing Big Data with Machine Learning in Precision Oncology.

While multi-level molecular "omic" analyses have undoubtedly increased the sophistication and depth with which we can understand cancer biology, the challenge is to make this overwhelming wealth of data relevant to the clinician and the individual patient. Bridging this gap serves as the cornerstone of precision medicine, yet the expense and difficulty of executing and interpreting these molecular studies make it impractical to routinely implement them in the clinical setting. Herein, we propose that machine learning may hold the key to guiding the future of precision oncology accurately and efficiently. Training deep learning models to interpret the histopathologic or radiographic appearance of tumors and their microenvironment-a phenotypic microcosm of their inherent molecular biology-has the potential to output relevant diagnostic, prognostic, and therapeutic patient-level data. This type of artificial intelligence framework may effectively shape the future of precision oncology by fostering multidisciplinary collaboration.