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Adjusting serum concentrations of organochlorine compounds by lipids and symptoms: A causal framework for the association with K-ras mutations in pancreatic cancer

机译:通过脂质和症状调整有机氯化合物的血清浓度:与胰腺癌K-ras突变相关的因果框架

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摘要

In clinically aggressive diseases, patients experience pathophysiological changes that often alter concentrations of lipids and environmental lipophilic factors; such changes are related to disease signs and symptoms. The aim of the study was to compare the effects of correcting for total serum lipids (TSL) and other clinical factors on the odds of mutations in the K-ras oncogene by organochlorine compounds (OCs), in logistic models, in 103 patients with exocrine pancreatic cancer (EPC) using a causal directed acyclic graph (DAG) framework. Results and likelihood of bias were discussed in the light of possible causal scenarios. The odds of K-ras mutated EPC was associated with some TSL-corrected OCs, including p,p′-DDT (p-value: 0.008) and polychlorinated biphenyl 138 (p-trend: 0.024). When OCs were not corrected by TSL, the OR of a K-ras mutation was significant for p,p′-DDT (p-trend: 0.035). Additionally adjusting for cholestatic syndrome increased the ORs of TSL-corrected OCs. When models were adjusted by the interval from first symptom to blood extraction (ISE), the ORs increased for both TSL-corrected and uncorrected OCs. Models with TSL-corrected OCs and adjusted for cholestatic syndrome or ISE yielded the highest ORs. We show that DAGs clarify the covariates necessary to minimize bias, and demonstrate scenarios under which adjustment for TSL-corrected OCs and failure to adjust for symptoms or ISE may induce bias. Models with TSL-uncorrected OCs may be biased too, and adjusting by symptoms or ISE may not control such biases. Our findings may have implications as well for studying environmental causes of other clinically aggressive diseases.
机译:在临床侵袭性疾病中,患者会经历病理生理变化,这些变化通常会改变脂质的浓度和环境亲脂性因子。这种变化与疾病的体征和症状有关。这项研究的目的是比较逻辑模型中103名外分泌患者中校正总血清脂质(TSL)和其他临床因素对有机氯化合物(OCs)导致K-ras癌基因突变的几率的影响使用因果无环图(DAG)框架的胰腺癌(EPC)。根据可能的因果情景讨论了偏差的结果和可能性。 K-ras突变的EPC的几率与某些TSL校正的OC相关,包括p,p'-DDT(p值:0.008)和多氯联苯138(p趋势:0.024)。当未通过TSL校正OC时,K-ras突变的OR对于p,p'-DDT显着(p趋势:0.035)。此外,针对胆汁淤积综合征进行调整会增加TSL校正的OC的OR。通过从第一症状到采血(ISE)的间隔调整模型后,TSL校正和未校正OC的OR均增加。经TSL校正的OC并针对胆汁淤积综合征或ISE进行调整的模型产生最高的OR。我们显示DAG阐明了使偏差最小化所必需的协变量,并演示了针对TSL校正的OC进行调整以及对症状或ISE进行调整失败可能导致偏差的方案。具有TSL未经校正的OC的模型也可能会产生偏差,并且通过症状或ISE进行调整可能无法控制此类偏差。我们的发现对于研究其他临床侵袭性疾病的环境原因也可能具有启示意义。

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