{"title":"化疗剂量强度对生存结果的因果影响:骨肉瘤的回顾性研究。","authors":"Marta Spreafico, Francesca Ieva, Marta Fiocco","doi":"10.1186/s12874-024-02416-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"24 1","pages":"296"},"PeriodicalIF":3.9000,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11613923/pdf/","citationCount":"0","resultStr":"{\"title\":\"Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma.\",\"authors\":\"Marta Spreafico, Francesca Ieva, Marta Fiocco\",\"doi\":\"10.1186/s12874-024-02416-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":9114,\"journal\":{\"name\":\"BMC Medical Research Methodology\",\"volume\":\"24 1\",\"pages\":\"296\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11613923/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Medical Research Methodology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12874-024-02416-x\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Research Methodology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12874-024-02416-x","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
摘要
背景:本研究旨在通过一种新颖的方法分析降低骨肉瘤患者化疗中接受剂量强度(RDI)对其生存的影响。先前的研究强调了计划和实际RDI之间的差异,即使在随机分配到相同治疗方案的患者中也是如此。为了减轻毒副作用,必须调整治疗,如减少剂量或延迟疗程。因此,毒性是死亡率的危险因素和未来接触水平的预测因素。在评估化疗RDI对生存结果的因果关系时,毒性引入了分配后的混淆,这是一个持续争论的话题。方法:采用BO03和BO06随机临床试验(rct)的骨肉瘤化疗给药数据,模拟三种基于RDI暴露策略的靶试验:1)标准,2)降低RDI, 3)高度降低RDI。研究在以组织学反应(HRe)差或好为特征的患者亚组之间进行,HRe是骨肉瘤患者生存的已知最强预后因素。首先利用处理加权逆概率(IPTW)将原始群体转化为模拟目标随机队列的伪群体。然后,采用效应修正的边际结构Cox模型。条件平均治疗效果(Conditional Average Treatment Effects, CATEs)最终被衡量为减少/高度减少RDI策略与标准策略的限制平均生存时间之间的差异。利用一种新颖的基于iptw的自举方法获得了CATEs的置信区间。结果:以HRe为基础的改良效果显著。rdi减少的增加导致了不良反应和良好反应的不同趋势:减少的越高,不良(良好)反应者的生存越好(越差)。由于对化疗的内在抗性,反应不良的患者可以从减少RDI中获益,减少和高度减少暴露的患者在5年的平均获益分别为10.2和15.4个月。结论:本研究引入了一种新的方法来(i)全面解决与化疗数据分析相关的挑战,(ii)减轻毒性-治疗-调整偏差,以及(iii)重新利用现有的RCT数据进行回顾性分析,扩展到原始试验的预期范围。
Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma.
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.
期刊介绍:
BMC Medical Research Methodology is an open access journal publishing original peer-reviewed research articles in methodological approaches to healthcare research. Articles on the methodology of epidemiological research, clinical trials and meta-analysis/systematic review are particularly encouraged, as are empirical studies of the associations between choice of methodology and study outcomes. BMC Medical Research Methodology does not aim to publish articles describing scientific methods or techniques: these should be directed to the BMC journal covering the relevant biomedical subject area.