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Biomarkers of Pro-Inflammatory Response May Identifiy Cancer Patients at Risk of Adverse Outcomes From SARS-CoV-2 Infection

Systemic inflammation is a key driver of mortality in SARS-CoV-2 in cancer patients and biomarkers of inflamation may be used to identify patients at increased risk
21 Nov 2020
Cancer in Special Situations / Population

Investigators testing and validating several key biomarkers of inflamation to identifiy cancer patients at increased risk of mortality from COVID-19 found a significant association between these biomarkers and decreased overall survival (OS). These findings were presented at the ESMO Asia Virtual Congress 2020, held from 20 to 22 November 2020.

Gino Dettorre, MRes, of the Department of Surgery and Cancer, Imperial College London - Hammersmith Hospital in London, UK, and colleagues were prompted by the understanding that systemic inflammation is common to both cancer progression and SARS-CoV-2 infection to determine whether inflammatory biomarkers can identify cancer patients with COVID-19 who are at risk of poorer outcome.

They conducted the OnCovid study, which retrospectively accrued 1,318 consecutive cancer patients infected with SARS-CoV-2 from 27 February to 23 June 2020 at 23 academic centres in the UK, Spain, Italy, Germany, and Belgium. Eligible patients were aged ≥18 and those with leukaemia, myeloma or insufficient data were excluded from the study.

The investigators evaluated neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), prognostic nutritional index (PNI), modified Glasgow prognostic score (mGPS), and prognostic index (PI) as prognostic biomarkers for increased risk. The NLR, PLR and PNI were dichotomised around their medians.

The validation set confirmed prognostic biomarkers evaluated in the training set

Of 1,071 patients, 529 were were sorted into a training set and 542 into a validation set. In the training and validation sets, respectively, patients were matched by age (67.9 ±13.3 versus 68.5 ±13.5), active malignancy at COVID-19 diagnosis (66.7% versus 61.6%), presence of >1 comorbidity (52.1% versus 49.8%), and prevalence of complications, including respiratory failure (58.0% versus 59.0%) and acute respiratory distress syndrome (ARDS; 11.5% versus 12.9%).

Asssessment of biomarkers in the training set showed that higher mortality rates were associated with NLR>6 (44.6% versus 28%; p < 0.0001), PNI<40 (46.6% versus 20.9%; p < 0.0001), mGPS (50.6% for mGPS2 versus 30.4% and 11.4% for mGPS1 and 0; p < 0.0001), and PI (50% for PI2 versus 40% for PI1 and 9.1% for PI0; p < 0.0001). Findings were confirmed in the validation set (p < 0.001).

The investigators found that patients in poor risk categories had significantly shorter median OS. Specifically, those with NLR>6 had median OS of 30 days (95% confidence interval [CI] 1-63), those with PNI<40 had median OS of 23 days (95% CI 10-35), mGPS2 corresponded with median OS of 20 days (95% CI 8-32), and patients with PI2 demonstrated median OS of 23 days (95% CI 1-56) compared to patients in good risk categories wherein median OS was not reached (p < 0.001 for all comparisons). No association between PLR and survival was found.

Analyses of survival in the validation set confirmed NLR (p < 0.0001), PNI (p < 0.0001), PI (p < 0.01) and mGPS (p < 0.001) as predictors of survival.

Finally, inflammatory markers’ hazard ratios (HRs) were compared in a multivariable Cox regression model with conditional backward elimination against each other and against previously established prognostic factors for COVID-19 outcome including sex, age, comorbid burden, malignancy status, and receipt of anti-cancer therapy at COVID-19 diagnosis. Among both inflammatory markers of interest and previously established prognostic factors, the PNI was the only factor to emerge with a statistically significant HR in both training (HR 1.97; 95% CI 1.19-3.26, p = 0.008) and validation set (HR 2.48; 95% CI 1.47-4.20, p = 0.001) analysis. Order of inflammatory indices’ prognostic relevance (shown in figure) was determined via Harrell’s C-index.


Following multivariable hazard ratio calculations and Harrell's C-index computation, patients with a poor risk PNI, a computation derived from hypoalbuminemia and lymphocytopenia, proved most susceptible to severe COVID-19. The mGPS (calculated via C-reactive protein levels and hypoalbuminemia), PI (calculated via C-reactive protein levels and leukocytosis), and NLR (the ratio of neutrophils to lymphocytes) emerged as most to least predictive of fatal COVID-19 respectively.

© Gino Dettorre.


According to the authors, these findings underscore that systemic inflammation is a key driver of mortality from SARS-CoV-2 in cancer patients and the NLR, PNI, mGPS, and PI are externally validated biomarkers that quantify systemic inflammation in patients with cancer and can be used as bedside tests to stratify patients at risk of poorer outcome from COVID-19, with an emphasis on hypoalbuminemia and lymphocytopenia as computed by the PNI.

This study was supported by the NIHR Imperial Biomedical Research Centre.


319O – Dettorre G, Diamantis N, Loizidou A, et al. The systemic pro-inflammatory response identifies cancer patients with adverse outcomes from SARS-CoV-2 infection. ESMO Asia Virtual Congress 2020 (20-22 November).

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