The evidence is not the average: why personalized therapies expose a structural limit in RCT logic.
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2026
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| _version_ | 1866901344248397824 |
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| author | Domargård, Anita |
| author_facet | Domargård, Anita |
| contents | <p>This Evidence Note examines a structural limitation in randomized controlled trial (RCT) logic when applied to personalized therapies.</p> <p>While RCTs estimate average treatment effects across populations, many emerging interventions—particularly in oncology—are inherently individualized. In these contexts, the assumption of comparability across patients breaks down. What appears as variability or inconsistency in outcomes may instead reflect structured, state-dependent responses within dynamic biological systems.</p> <p>Drawing on clinical epidemiology, oncology, systems biology, and decision science, this work reframes treatment response as an emergent property of system state and trajectory rather than a fixed effect of an intervention. The note introduces state-dependence as a central principle for interpreting treatment effects, extending beyond traditional discussions of heterogeneity.</p> <p>Within the Universal Resonance Model (URM), disease is understood as a dynamic system in which signal meaning changes over time. From this perspective, the challenge is not a lack of rigor in evidence generation, but a mismatch between static methodologies and evolving biological processes.</p> <p>The implications are both methodological and clinical. Averaging effects across populations may obscure meaningful signals, increase false negatives, and misclassify effective therapies. Clinically, treatment decisions require interpretation of trajectory and timing, not only endpoint outcomes.</p> <p>This note contributes to the ongoing shift from population-based inference toward dynamic, context-sensitive models of clinical evidence.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19650951 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The evidence is not the average: why personalized therapies expose a structural limit in RCT logic. Domargård, Anita Personalized medicine Randomized controlled trials Treatment heterogeneity State-dependent response Systems medicine Dynamic disease; Clinical decision-making Treatment timing Biological variability Precision oncology Causal inference Universal Resonance Model (URM) Medicine Rheumatology Systems Biology Computer and Information Science Clinical Medicine Epidemiology <p>This Evidence Note examines a structural limitation in randomized controlled trial (RCT) logic when applied to personalized therapies.</p> <p>While RCTs estimate average treatment effects across populations, many emerging interventions—particularly in oncology—are inherently individualized. In these contexts, the assumption of comparability across patients breaks down. What appears as variability or inconsistency in outcomes may instead reflect structured, state-dependent responses within dynamic biological systems.</p> <p>Drawing on clinical epidemiology, oncology, systems biology, and decision science, this work reframes treatment response as an emergent property of system state and trajectory rather than a fixed effect of an intervention. The note introduces state-dependence as a central principle for interpreting treatment effects, extending beyond traditional discussions of heterogeneity.</p> <p>Within the Universal Resonance Model (URM), disease is understood as a dynamic system in which signal meaning changes over time. From this perspective, the challenge is not a lack of rigor in evidence generation, but a mismatch between static methodologies and evolving biological processes.</p> <p>The implications are both methodological and clinical. Averaging effects across populations may obscure meaningful signals, increase false negatives, and misclassify effective therapies. Clinically, treatment decisions require interpretation of trajectory and timing, not only endpoint outcomes.</p> <p>This note contributes to the ongoing shift from population-based inference toward dynamic, context-sensitive models of clinical evidence.</p> |
| title | The evidence is not the average: why personalized therapies expose a structural limit in RCT logic. |
| topic | Personalized medicine Randomized controlled trials Treatment heterogeneity State-dependent response Systems medicine Dynamic disease; Clinical decision-making Treatment timing Biological variability Precision oncology Causal inference Universal Resonance Model (URM) Medicine Rheumatology Systems Biology Computer and Information Science Clinical Medicine Epidemiology |
| url | https://doi.org/10.5281/zenodo.19650951 |