Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma
Abstract Background This study aims to analyse the effects of reducing Received Dose Intensity (RDI) in chemotherapy treatment for osteosarcoma patients on their survival by using a novel approach. Previous research has highlighted discrepancies between planned and actual RDI, even among patients ra...
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BMC
2024-12-01
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| Series: | BMC Medical Research Methodology |
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| Online Access: | https://doi.org/10.1186/s12874-024-02416-x |
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| author | Marta Spreafico Francesca Ieva Marta Fiocco |
| author_facet | Marta Spreafico Francesca Ieva Marta Fiocco |
| author_sort | Marta Spreafico |
| collection | DOAJ |
| description | Abstract Background This study aims to analyse the effects of reducing Received Dose Intensity (RDI) in chemotherapy treatment for osteosarcoma patients on their survival by using a novel approach. Previous research has highlighted discrepancies between planned and actual RDI, even among patients randomized to the same treatment regimen. To mitigate toxic side effects, treatment adjustments, such as dose reduction or delayed courses, are necessary. Toxicities are therefore risk factors for mortality and predictors of future exposure levels. Toxicity introduces post-assignment confounding when assessing the causal effect of chemotherapy RDI on survival outcomes, a topic of ongoing debate. Methods Chemotherapy administration data from BO03 and BO06 Randomized Clinical Trials (RCTs) in ostosarcoma are employed to emulate a target trial with three RDI-based exposure strategies: 1) standard, 2) reduced, and 3) highly-reduced RDI. Investigations are conducted between subgroups of patients characterised by poor or good Histological Responses (HRe), i.e., the strongest known prognostic factor for survival in osteosarcoma. Inverse Probability of Treatment Weighting (IPTW) is first used to transform the original population into a pseudo-population which mimics the target randomized cohort. Then, a Marginal Structural Cox Model with effect modification is employed. Conditional Average Treatment Effects (CATEs) are ultimately measured as the difference between the Restricted Mean Survival Time of reduced/highly-reduced RDI strategy and the standard one. Confidence Intervals for CATEs are obtained using a novel IPTW-based bootstrap procedure. Results Significant effect modifications based on HRe were found. Increasing RDI-reductions led to contrasting trends for poor and good responders: the higher the reduction, the better (worsen) was the survival in poor (good) reponders. Due to their intrinsic resistance to chemotherapy, poor reponders could benefit from reduced RDI, with an average gain of 10.2 and 15.4 months at 5-year for reduced and highly-reduced exposures, respectively. Conclusions This study introduces a novel approach to (i) comprehensively address the challenges related to the analysis of chemotherapy data, (ii) mitigate the toxicity-treatment-adjustment bias, and (iii) repurpose existing RCT data for retrospective analyses extending beyond the original trials’ intended scopes. |
| format | Article |
| id | doaj-art-176b64d97a734d5296f4f68c4e9ca7be |
| institution | OA Journals |
| issn | 1471-2288 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj-art-176b64d97a734d5296f4f68c4e9ca7be2025-08-20T02:31:03ZengBMCBMC Medical Research Methodology1471-22882024-12-0124111810.1186/s12874-024-02416-xCausal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcomaMarta Spreafico0Francesca Ieva1Marta Fiocco2Mathematical Institute, Leiden UniversityMOX – Department of Mathematics, Politecnico di MilanoMathematical Institute, Leiden UniversityAbstract Background This study aims to analyse the effects of reducing Received Dose Intensity (RDI) in chemotherapy treatment for osteosarcoma patients on their survival by using a novel approach. Previous research has highlighted discrepancies between planned and actual RDI, even among patients randomized to the same treatment regimen. To mitigate toxic side effects, treatment adjustments, such as dose reduction or delayed courses, are necessary. Toxicities are therefore risk factors for mortality and predictors of future exposure levels. Toxicity introduces post-assignment confounding when assessing the causal effect of chemotherapy RDI on survival outcomes, a topic of ongoing debate. Methods Chemotherapy administration data from BO03 and BO06 Randomized Clinical Trials (RCTs) in ostosarcoma are employed to emulate a target trial with three RDI-based exposure strategies: 1) standard, 2) reduced, and 3) highly-reduced RDI. Investigations are conducted between subgroups of patients characterised by poor or good Histological Responses (HRe), i.e., the strongest known prognostic factor for survival in osteosarcoma. Inverse Probability of Treatment Weighting (IPTW) is first used to transform the original population into a pseudo-population which mimics the target randomized cohort. Then, a Marginal Structural Cox Model with effect modification is employed. Conditional Average Treatment Effects (CATEs) are ultimately measured as the difference between the Restricted Mean Survival Time of reduced/highly-reduced RDI strategy and the standard one. Confidence Intervals for CATEs are obtained using a novel IPTW-based bootstrap procedure. Results Significant effect modifications based on HRe were found. Increasing RDI-reductions led to contrasting trends for poor and good responders: the higher the reduction, the better (worsen) was the survival in poor (good) reponders. Due to their intrinsic resistance to chemotherapy, poor reponders could benefit from reduced RDI, with an average gain of 10.2 and 15.4 months at 5-year for reduced and highly-reduced exposures, respectively. Conclusions This study introduces a novel approach to (i) comprehensively address the challenges related to the analysis of chemotherapy data, (ii) mitigate the toxicity-treatment-adjustment bias, and (iii) repurpose existing RCT data for retrospective analyses extending beyond the original trials’ intended scopes.https://doi.org/10.1186/s12874-024-02416-xMarginal structural Cox modelsInverse Probability of treatment weightingEffect modificationTarget trial emulationReceived dose intensityChemotherapy |
| spellingShingle | Marta Spreafico Francesca Ieva Marta Fiocco Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma BMC Medical Research Methodology Marginal structural Cox models Inverse Probability of treatment weighting Effect modification Target trial emulation Received dose intensity Chemotherapy |
| title | Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma |
| title_full | Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma |
| title_fullStr | Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma |
| title_full_unstemmed | Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma |
| title_short | Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma |
| title_sort | causal effect of chemotherapy received dose intensity on survival outcome a retrospective study in osteosarcoma |
| topic | Marginal structural Cox models Inverse Probability of treatment weighting Effect modification Target trial emulation Received dose intensity Chemotherapy |
| url | https://doi.org/10.1186/s12874-024-02416-x |
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