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Jasmin Hundal: Bridging the Gap Between Clinical Trials and Real-World Patients in Oncology

Jasmin Hundal/X

Jan 7, 2025, 13:06

Jasmin Hundal: Bridging the Gap Between Clinical Trials and Real-World Patients in Oncology

Jasmin Hundal, Hematology-Oncology Fellow at Cleveland Clinic and also a Resident Physician at the University of Connecticut, shared a recent article by Xavier Orcutt on LinkedIn:

“Bridging the Gap Between Clinical Trials and Real-World Patients in Oncology.

Clinical trials are essential for advancing oncology treatments, but their results often lack generalizability to real-world patients.

This disconnect can lead to disparities in treatment outcomes and underrepresentation of patients with higher prognostic risk.

A recent study by Xavier Orcutt et al., published in Nature Medicine, introduces Trial Translator, a machine learning-based framework designed to emulate oncology trials and evaluate their applicability across diverse patient populations.

Key Findings:

Patients with low- and medium-risk profiles experienced survival benefits similar to those reported in randomized controlled trials.
High-risk patients (greater comorbidities or poorer prognoses) showed significantly lower survival and reduced benefit from standard therapies.
Trial Translator successfully identified prognostic phenotypes that better reflect the heterogeneity of real-world patients.

Why Does This Matter?

Restrictive eligibility criteria alone do not explain the generalizability gap.
Prognostic risk, socioeconomic factors, and selection biases influence trial outcomes.

This study integrates real-world data from Flatiron Health with ML-driven phenotyping to highlight the importance of designing trials that more accurately reflect patient diversity

Implications for Oncology:

Trial design: Risk stratification can improve inclusivity in future RCTs.
Clinical practice: Oncologists can use tools like Trial Translator to estimate the real-world benefits of therapies for their patients.
Regulatory frameworks: Encouraging broader eligibility and pragmatic trials can enhance equitable access to novel therapies

This paper represents a step forward in aligning clinical research with real-world practice to ensure more personalized and effective cancer care.

How can we further address this disconnect in clinical research?”

Evaluating the generalizability of oncology trial results to real-world patients using machine learning-based trial emulations

Authors: Xavier Orcutt, Kan Chen, Ronac Mamtani, Qi Long and Ravi B. Parikh

Jasmin Hundal-Clinical Trials

Jasmin Hundal is a Hematology Oncology Fellow at Cleveland Clinic and a board-certified internal medicine physician. She is also a Resident Physician at the University of Connecticut. Her research centers on the impact of modifiable risk factors like diet, metabolism, and the microbiome on cancer and its treatment.

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Jasmin Hundal: Bridging the Gap Between Clinical Trials and Real-World Patients in Oncology