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Inflammatory Biomarker Score Identifies Patients with Six-Fold Increased Risk of One-Year Mortality after Pancreatic Cancer.

ABSTRACT: We examined whether elevated plasma C-reactive protein (CRP), carbohydrate antigen (CA) 19-9, interleukin-6 (IL-6) and YKL-40, individually or combined, can identify poor survivors among patients with pancreatic ductal adenocarcinoma (PDAC). We measured CRP, CA 19-9, IL-6 and YKL-40 in 993 patients at the time of PDAC diagnosis. The biomarker score was the sum of biomarker categories, coded 0, 1 and 2 for low, intermediate and high plasma concentrations, respectively. High vs. low levels of CRP, CA 19-9 and IL-6 were each independently associated with a two-fold increased risk of one-year mortality. CRP performed best in patients with advanced and CA 19-9 in patients with low cancer stages. YKL-40 was not associated with mortality and, therefore, was not included in the biomarker score. Compared to the biomarker score = 0, the multifactorially adjusted hazard ratios for one-year mortality were 1.56 (95% confidence interval: 0.99-2.44) for score = 1, 2.22 (1.41-3.49) for score = 2, 3.44 (2.20-5.38) for score = 3, 5.13 (3.21-8.17) for score = 4 and 6.32 (3.84-10.41) for score = 5-6 (p-value for trend = 3 × 10^-31). This score performed better than any single biomarker or combination of biomarkers when examined in similarly sized or other categories. In conclusion, a combination score of elevated CRP, CA 19-9 and IL-6 identified patients with six-fold higher one-year mortality.

SUBMITTER: Kjaergaard AD

PROVIDER: S-EPMC8466571 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeSurvival among patients with adenocarcinoma pancreatic cancer (PDCA) is highly variable, which ranges from 0% to 20% at 5 years. Such a wide range is due to tumor size and stage, as well other patients' characteristics. We analyzed alterations in the metabolomic profile, of PDCA patients, which are potentially predictive of patient's one-year mortality.Experimental designA targeted metabolomic assay was conducted on serum samples of patients diagnosed with pancreatic cancer. Statistical analyses were performed only for those 27 patients with information on vital status at follow-up and baseline clinical features. Random Forest analysis was performed to identify all metabolites and clinical variables with the best capability to predict patient's mortality risk at one year. Regression coefficients were estimated from multivariable Weibull survival model, which included the most associated metabolites. Such coefficients were used as weights to build a metabolite risk score (MRS) which ranged from 0 (lowest mortality risk) to 1 (highest mortality risk). The stability of these weights were evaluated performing 10,000 bootstrap resamplings.ResultsMRS was built as a weighted linear combination of the following five metabolites: Valine (HR = 0.62, 95%CI: 0.11-1.71 for each standard deviation (SD) of 98.57), Sphingomyeline C24:1 (HR = 2.66, 95%CI: 1.30-21.09, for each SD of 20.67), Lysine (HR = 0.36, 95%CI: 0.03-0.77, for each SD of 51.73), Tripentadecanoate TG15 (HR = 0.25, 95%CI: 0.01-0.82, for each SD of 2.88) and Symmetric dimethylarginine (HR = 2.24, 95%CI: 1.28-103.08, for each SD of 0.62), achieving a very high discrimination ability (survival c-statistic of 0.855, 95%CI: 0.816-0.894). Such association was still present even after adjusting for the most associated clinical variables (confounders).ConclusionsThe mass spectrometry-based metabolomic profiling of serum represents a valid tool for discovering novel candidate biomarkers with prognostic ability to predict one-year mortality risk in patients with pancreatic adenocarcinoma.

Project description:Background Mortality is increased following a hospitalization for decompensated heart failure (HF), during which diuretics are usually intensified. It is unclear how risk is affected after outpatient intensification of diuretic therapy for HF. Methods and Results From nationwide administrative registers, we identified all Danish patients who were diagnosed with HF from 2001 to 2016 and received angiotensin-converting enzyme inhibitor/angiotensin receptor blocker and β blocker within 120 days. Subsequent follow-up tracked progressive events of diuretic intensification and HF hospitalization. Intensification events were defined as new addition or doubling of loop diuretic or addition of thiazide to loop diuretic. These events were included in multivariable Cox regression models, calculating 1-year mortality hazard after each year since inclusion. Patients with an intensification event or hospitalization were risk set matched to 2 nonworsened HF controls and absolute 1-year mortality risks were calculated using Kaplan-Meier estimates. We included 74 990 patients, their median age was 71 years, and 36% were women. Intensification events were associated with significantly increased mortality at all times during follow-up. One-year mortality was 18.0% after an intensification event, 22.6% after HF hospitalization, and 10.4% for matched controls with neither. In a multivariable Cox model adjusted for age, sex, ischemic heart disease, atrial fibrillation, chronic obstructive pulmonary disease, and diabetes mellitus, the hazard ratio for 1-year death after an intensification event was 1.75 (95% CI, 1.66-1.85), and it was 2.28 (95% CI, 2.16-2.41) after HF hospitalization. Conclusions In a nationwide cohort of patients with HF, outpatient intensification events were associated with almost 2-fold risk of mortality during the next year. Although HF hospitalization was associated with a higher risk, the need to intensify diuretics in the outpatient setting is a signal to review and intensify efforts to improve HF outcomes.

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Inflammatory Biomarker Score Identifies Patients with Six-Fold Increased Risk of One-Year Mortality after Pancreatic Cancer.

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