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This study aims to analyse the effects of reducing Received Dose Intensity(RDI) in chemotherapy treatment for osteosarcoma patients on their survival byusing a novel approach. In this scenario, toxic side effects are risk factorsfor mortality and predictors of future exposure levels, introducingpost-assignment confounding.  Chemotherapy administration data from BO03 and BO06 Randomized ClinicalTrials (RCTs) in ostosarcoma are employed to emulate a target trial with threeRDI-based exposure strategies: 1) standard, 2) reduced, and 3) highly-reducedRDI. Investigations are conducted between subgroups of patients characterisedby poor or good Histological Responses (HRe). Inverse Probability of TreatmentWeighting (IPTW) is first used to transform the original population into apseudo-population which mimics the target randomized cohort. Then, a MarginalStructural Cox Model with effect modification is employed. Conditional AverageTreatment Effects (CATEs) are ultimately measured as the difference between theRestricted Mean Survival Time of reduced/highly-reduced RDI strategy and thestandard one. Confidence Intervals for CATEs are obtained using a novelIPTW-based bootstrap procedure.  Significant effect modifications based on HRe were found. IncreasingRDI-reductions led to contrasting trends for poor and good responders: thehigher the reduction, the better (worsen) was the survival in poor (good)reponders. This study introduces a novel approach to (i) comprehensivelyaddress the challenges related to the analysis of chemotherapy data, (ii)mitigate the toxicity-treatment-adjustment bias, and (iii) repurpose existingRCT data for retrospective analyses extending beyond the original trials'intended scopes.

Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma