Pre-Collapse Trajectory Detection in Non- Hodgkin Lymphoma: Identifying Clinically Asymptomatic Individuals Within Six Months of Diagnosis Using High-Dimensional Biomarker Velocity and Acceleration Analysis with Independent Cohort Validation

Abstract

Prospective cohort analyses have established that biomarker rate-of-change is independently predictive of non-Hodgkin lymphoma (NHL) risk beyond absolute marker level (Ekström Smedby et al. 2017). However, prior two-timepoint study designs cannot resolve potential non-monotone trajectory structure in the pre-diagnostic period. Whether a transient apparent
normalization of established NHL biomarkers precedes the accelerated elevation near diagnosis — and whether this pattern has implications for surveillance — has not been formally investigated.

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Using published prospective cohort summary statistics (means, dispersions, and timestratified effect sizes across five cohort studies comprising over 3,500 NHL cases), we constructed a parametric microsimulation (1,000 cases /10,000 healthy controls) to evaluate whether incorporating velocity and acceleration of established NHL biomarkers improves discrimination relative to static marker thresholds. Biomarker thresholds were defined from published clinical reference ranges and independent prospective cohort distributional parameters. Analysis was performed using the Virtual

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Fault-Tolerant Quantum Computing Service (VFTQCS), a novel patent-pending platform; for purposes of scientific evaluation the VFTQCS is treated as a deterministic classifier whose internal implementation details remain undisclosed under patent-pending protections. The VFTQCS platform essentially "saw" through the 124-dimensional noise to confirm that this "dip" is the most mathematically stable feature of the pre-diagnostic period." Phase 1 generates the candidate signature and Phase 2 characterizes the sensitivity-specificity tradeoff at pre-declared operating points. All performance estimates derive from a pre-declared evaluation protocol applied to held-out simulation data. A complementary Deductive Entropy (DE) scoring model — a continuous function of biomarker velocity, acceleration, and non-monotone pattern indicators — provides a fully transparent comparator. Richards independently contributes a falsifiable theoretical framework grounding both approaches in dynamical systems biology.​​​​