IL-6 and CRP provide only a limited increase

IL-6 and CRP provide only a limited increase

While IL-6 and CRP rise early after lung cancer surgery, new research shows that the added value for predicting infections remains small, highlighting the need for better early warning tools.

A current onePLOS oneThe study examined the potential of IL-6 as a biomarker to predict the risk of infection after surgery.

Infection risks after lung cancer surgery

Approximately 20% of patients who have undergone lung cancer surgery develop a postoperative infection, potentially progressing to sepsis. These infections adversely affect treatment outcomes and may even increase mortality rates. Many studies have shown that patients who survive sepsis may develop persistent functional disability. To prevent adverse postoperative sequelae, it is essential to provide these patients with timely antibiotic treatment.

Early identification of patients who are more susceptible to developing postoperative infections could be beneficial as these individuals can be closely monitored for signs of postoperative infection.

Postoperative hyperinflammation could be a valuable predictor to determine these patients. After surgery, damaging molecular patterns (DAMPs) are released to trigger the innate immune system, which facilitates both pro- and anti-inflammatory responses to promote tissue healing and prevent microbial infections. However, some patients develop an excessive inflammatory response to surgery, leading to hyperinflammation that increases infection risks.

IL-6 and C-reactive protein (CRP) are common inflammatory biomarkers associated with severe injury. Many studies have shown that IL-6 reaches peak concentrations more quickly and has a shorter plasma half-life after surgery compared to CRP. In contrast, CRP concentrations are maximized almost three days after surgery.

IL-6 could be exploited as a biomarker to identify patients at higher risk of developing postoperative infections, allowing timely antibiotic intervention to prevent serious infections. To date, only a few studies have examined the potential of IL-6 as a predictor of postoperative infection in pulmonary surgery.

About the study

A prospective, two-center observational study was conducted at Amphia Hospital Breda and Sint Antonius Hospital Nieuwegein, Netherlands, to evaluate postoperative hyperinflammation based on maximal IL-6 concentrations. In addition to IL-6, the infection-specific capacity of CRP, white blood cell (WBC) count, and procalcitonin (PCT) were also assessed.

In this study, participants were recruited between September 3, 2018 and April 29, 2022. All selected participants underwent elective lung surgery for cancer with a planned postoperative intensive care unit (ICU) admission. Blood samples were obtained at various time points, including after induction of general anesthesia (preoperative sample) and at 6, 9, 12, 24, 48, and 72 hours (postoperative samples). Plasma levels of IL-6, CRP and PCT were measured using a standard protocol.

The development of various postoperative infections (e.g., respiratory tract infections, urinary tract infections, empyema, or sepsis) within 30 days after surgery was monitored.

A core model was developed based on various variables including age, gender, duration of surgery, and Charlson Comorbidity Index (CCI). The predictive value of inflammatory biomarkers within 24 hours of the start of surgery was evaluated compared to the core model.

Study results

A total of 170 patients were included in this study with a mean age of 67 years. 45% of the study cohort consisted of women. CCI was ≥3 of 30 (18%) patients. The majority of the study cohort underwent minimally invasive surgery using video-assisted thoracoscopes (VATS), robot-assisted thoracoscopic surgery (rats), lobectomy, or sleeve resection. The mean operative time was 193 minutes, and approximately 89% of patients received dexamethasone for PONV prophylaxis.

In this study, 22% of the cohort developed a postoperative infection. It is worth noting that some patients developed more than one infection. Most infections were associated with the respiratory system (74%), followed by surgical site infections (18%) and urinary tract infections (8%). Seven patients developed postoperative sepsis. The median time for diagnosis of infection was four days after surgery.

Approximately 66% of infections were diagnosed in the first week after surgery. Typically, patients who underwent longer surgery, had more intraoperative blood loss, and were less likely to receive IV dexamethasone were more susceptible to infection.

Compared to uninfected patients, higher preoperative concentrations of IL-6 and CRP were found in patients with postoperative infection. In most patients, postoperative IL-6 concentrations peaked within six hours, while peak CRP concentrations were reached three days after surgery.

It is worth noting that the mean maximum concentrations of IL-6 and CRP within 24 hours after surgery were higher in patients with postoperative infections. However, WBC and PCT showed no predictive capacity.

In the current study, IL-6 was indeed found to be associated with postoperative infection, independent of the core model predictors. Similarly, peak CRP concentrations were also associated with postoperative infection. While both biomarkers significantly improved model fit after statistical testing, this did not result in a meaningful improvement in practical prediction.

In particular, the model's ability to distinguish between patients who would contract with infection and patients who would not (as measured by the C-statistic). Both PCT and WBC failed to improve model fit.

Furthermore, adding IL-6 to the core model did not improve the classification of infected patients, while adding CRP actually worsened the classification for this group. While both improved the classification of uninfected patients, the overall benefit was negligible.

Conclusions

The main takeaway from the current study is that early postoperative plasma IL-6 and CRP concentrations were independently associated with the risk of subsequent infection, the added value of these biomarkers for a simple clinical prediction model appears to be limited. The authors concluded that none of the biomarkers substantially improved prognostic classification when added to a model with readily available clinical data.

The study highlighted some important limitations beyond the need for a larger cohort. The limited sample size resulted in wide confidence intervals for the performance measures, meaning that a moderate incremental value may have been missed.

Additionally, the study was too small to analyze predictive performance compared to whether patients had open versus minimally invasive surgeries, a known factor that influences inflammation. Finally, the authors note that the selected times for blood sampling may not coincide with the exact peak concentration of IL-6 for each patient.

Therefore, the study concludes that the results need to be validated in future and larger research before definitive conclusions can be drawn about the clinical utility of either biomarker.

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