TY - JOUR
T1 - Value of Real-World Evidence for Treatment Selection
T2 - A Case Study in Colon Cancer
AU - Shen, Lingjie
AU - van Gestel, Anja
AU - Prinsen, Peter
AU - Vink, Geraldine
AU - van Erning, Felice N.
AU - Geleijnse, Gijs
AU - Kaptein, Maurits
N1 - Publisher Copyright:
© 2024 by American Society of Clinical Oncology.
PY - 2024/5/15
Y1 - 2024/5/15
N2 - PURPOSE Real-world evidence (RWE)—derived from analysis of real-world data (RWD)—has the potential to guide personalized treatment decisions. However, because of potential confounding, generating valid RWE is challenging. This study demonstrates how to responsibly generate RWE for treatment decisions. We validate our approach by demonstrating that we can uncover an existing adjuvant chemotherapy (ACT) guideline for stage II and III colon cancer (CC)—which came about using both data from randomized controlled trials and expert consensus—solely using RWD. METHODS Data from the population-based Netherlands Cancer Registry from a total of 27,056 patients with stage II and III CC who underwent curative surgery were analyzed to estimate the overall survival (OS) benefit of ACT. Focusing on 5-year OS, the benefit of ACT was estimated for each patient using G-computation methods by adjusting for patient and tumor characteristics and estimated propensity score. Subsequently, on the basis of these estimates, an ACT decision tree was constructed. RESULTS The constructed decision tree corresponds to the current Dutch guideline: patients with stage III or stage II with T stage 4 should receive surgery and ACT, whereas patients with stage II with T stage 3 should only receive surgery. Interestingly, we do not find sufficient RWE to conclude against ACT for stage II with T stage 4 and microsatellite instability-high (MSI-H), a recent addition to the current guideline. CONCLUSION RWE, if used carefully, can provide a valuable addition to our construction of evidence on clinical decision making and therefore ultimately affect treatment guidelines. Next to validating the ACT decisions advised in the current Dutch guideline, this paper suggests additional attention should be paid to MSI-H in future iterations of the guideline.
AB - PURPOSE Real-world evidence (RWE)—derived from analysis of real-world data (RWD)—has the potential to guide personalized treatment decisions. However, because of potential confounding, generating valid RWE is challenging. This study demonstrates how to responsibly generate RWE for treatment decisions. We validate our approach by demonstrating that we can uncover an existing adjuvant chemotherapy (ACT) guideline for stage II and III colon cancer (CC)—which came about using both data from randomized controlled trials and expert consensus—solely using RWD. METHODS Data from the population-based Netherlands Cancer Registry from a total of 27,056 patients with stage II and III CC who underwent curative surgery were analyzed to estimate the overall survival (OS) benefit of ACT. Focusing on 5-year OS, the benefit of ACT was estimated for each patient using G-computation methods by adjusting for patient and tumor characteristics and estimated propensity score. Subsequently, on the basis of these estimates, an ACT decision tree was constructed. RESULTS The constructed decision tree corresponds to the current Dutch guideline: patients with stage III or stage II with T stage 4 should receive surgery and ACT, whereas patients with stage II with T stage 3 should only receive surgery. Interestingly, we do not find sufficient RWE to conclude against ACT for stage II with T stage 4 and microsatellite instability-high (MSI-H), a recent addition to the current guideline. CONCLUSION RWE, if used carefully, can provide a valuable addition to our construction of evidence on clinical decision making and therefore ultimately affect treatment guidelines. Next to validating the ACT decisions advised in the current Dutch guideline, this paper suggests additional attention should be paid to MSI-H in future iterations of the guideline.
UR - http://www.scopus.com/inward/record.url?scp=85193328939&partnerID=8YFLogxK
U2 - 10.1200/CCI.23.00186
DO - 10.1200/CCI.23.00186
M3 - Article
C2 - 38753347
AN - SCOPUS:85193328939
SN - 2473-4276
VL - 8
JO - JCO clinical cancer informatics
JF - JCO clinical cancer informatics
M1 - e2300186
ER -