Prognostic Factors in Colorectal Cancer: Serum LDH Levels Predict Survival in Metastatic Disease

Najib, Rajae; Daoudi, Khalid; Zahra, Hijri Fatima; Arifi, Samia; Mellas, Nawfel

doi:10.1093/annonc/mdu165.212

Cited by 1 publication

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“…Elevated levels of LDH in the blood can be indicative of tissue damage or disease, and have been associated with poor prognosis in several types of cancer 4,17,18 . Research has suggested that LDH levels can be a prognostic factor for CRC, especially in metastatic disease 5,19 . So far, prognostic models of survival have often relied on pretreatment baseline LDH, and very few models link survival to longitudinal LDH measured repeatedly over time during treatment.…”

Section: Discussionmentioning

confidence: 99%

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Evaluating Prognostic Value of Dynamics of Circulating Lactate Dehydrogenase in Colorectal Cancer Using Modeling and Machine Learning

Ding,

Yuan,

Yang

et al. 2023

Clin Pharma and Therapeutics

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Pre‐treatment serum lactate dehydrogenase (LDH) levels have been associated with poor prognosis in several types of cancer, including metastatic colorectal cancer (mCRC). However, very few models link survival to longitudinal LDH measured repeatedly over time during treatment. We investigated the prognostic value of on‐treatment LDH dynamics in mCRC. Using data from two large Phase III studies (2L and 3L+ mCRC settings, n = 824 and 210, respectively), we found that integrating longitudinal LDH data with baseline risk factors significantly improved survival prediction. Current LDH values performed best, enhancing discrimination ability (area under the receiver operating characteristic curve) by 4.5% ~ 15.4% and prediction accuracy (Brier score) by 3.9% ~ 15.0% compared to baseline variables. Combining all four longitudinal LDH markers further improved predictive performance. After controlling for baseline covariates and other longitudinal LDH indicators, current LDH levels remained a significant risk factor in mCRC, increasing mortality risk by over 90% (P < 0.001) in 2L patients and 60‐70% (P < 0.01) in 3L+ patients per unit increment in current log(LDH). Machine learning techniques like functional principal component analysis (FPCA) extracted informative features from longitudinal LDH data, capturing over 99% of variability and allowing prediction of survival. Unsupervised clustering based on the extracted FPCA features stratified patients into three groups with distinct LDH dynamics and survival outcomes. Hence, our approaches offer a valuable and cost‐effective way for risk stratification and improves survival prediction in mCRC using LDH trajectories.

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Section: Discussionmentioning

confidence: 99%

“…4,17,18 Research has suggested that LDH levels can be a prognostic factor for CRC, especially in metastatic disease. 5,19 So far, prognostic models of survival have often relied on pretreatment baseline LDH, and very few models link survival to longitudinal LDH measured repeatedly over time during treatment.…”

Section: Articlementioning

confidence: 99%

Evaluating Prognostic Value of Dynamics of Circulating Lactate Dehydrogenase in Colorectal Cancer Using Modeling and Machine Learning

Ding,

Yuan,

Yang

et al. 2023

Clin Pharma and Therapeutics

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Prognostic Factors in Colorectal Cancer: Serum LDH Levels Predict Survival in Metastatic Disease

Abstract: Introduction: Lactate dehydrogenase (LDH) is a product regulates the anaerobic transformation of pyruvate to lactate for energy acquisition. The significance of serum

Cited by 1 publication

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Evaluating Prognostic Value of Dynamics of Circulating Lactate Dehydrogenase in Colorectal Cancer Using Modeling and Machine Learning

Evaluating Prognostic Value of Dynamics of Circulating Lactate Dehydrogenase in Colorectal Cancer Using Modeling and Machine Learning

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