Background: The underlying changes of peripheral blood inflammatory cells (PBICs) in COVID-19 patients are little known. Moreover, the risk factors for the underlying changes of PBICs and their predicting role in severe COVID-19 patients remain uncertain. Material and methods: This retrospective study including two cohorts: the main cohort enrolling 45 patients of severe type serving as study group, and the secondary cohort enrolling 12 patients of no-severe type serving as control group. The PBICs analysis was based on blood routine and lymphocyte subsets. The inflammatory cell levels were compared among patients according to clinical classifications, disease-associated phases, as well as one-month outcomes. Results: Compared with patients of non-severe type, the patients of severe type suffered from significantly decreased counts of lymphocytes, eosinophils, basophils, but increased counts of neutrophils. These PBICs alterations got improved in recovery phase, but persisted or got worse in aggravated phase. Compared with patients in discharged group, the patients in un-discharged/died group suffered from decreased counts of total T lymphocytes, CD4 + T lymphocytes, CD8 + T lymphocytes, as well as NK cells at 2 weeks after treatment. Clinical classification-critically severe was the independently risk factor for lymphopenia (OR = 7.701, 95%CI:1.265-46.893, P = 0.027), eosinopenia (OR = 5.595, 95%CI:1.008-31.054, P = 0.049), and worse onemonth outcome (OR = 8.984; 95%CI:1.021-79.061, P = 0.048). Conclusion: Lymphopenia and eosinopenia may serve as predictors of disease severity and disease progression in COVID-19 patients, and enhancing the cellular immunity may contribute to COVID-19 treatment. Thus, PBICs might become a sentinel of COVID-19, and it deserves attention during COVID-19 treatment. IntroductionSince December 2019, an increasing number of pneumonia cases emerged in Wuhan, and rapidly spread throughout China [1]. The causative virus was officially named as 2019-novel coronavirus (2019-nCoV), and its relevant infected disease was also officially designated

Background Geriatric Nutritional Risk Index (GNRI) has been widely used to assess the nutritional status in a variety of human pathological conditions, but the prognostic value of the GNRI in malignancies has not been evinced. Methods Relevant studies updated on Jul 27, 2019, were retrieved in available databases, including PubMed, Web of Science, Cochrane library, Chinese CNKI, and Chinese Wan-fang. Hazard ratios (HRs) and 95% confidence intervals (CIs) were extracted and pooled by using STATA 14. Results A total of 15 studies involving 8,046 subjects were included in this meta-analysis. Meta-analysis results evinced that low GNRI was associated with poor OS (HR = 1.95, 95% CI: 1.49-2.56, p ≤ 0.001), poor CSS (HR = 1.81, 95% CI: 1.49-2.19, p ≤ 0.001), poor DFS (HR = 1.67, 95% CI: 1.28-2.17, p ≤ 0.001), and poor PFS (HR = 1.68, 95% CI: 1.28-2.21, p ≤ 0.001), and the correlation of GNRI with OS was not changed when stratified by possible confounding factors, suggesting that malignancy patients with low GNRI would suffer from reduced survival rate and increased recurrence rate. Moreover, low GNRI was also associated with postoperative complications in malignancies. Conclusions In summary, GNRI is associated poor prognosis in human malignancies, and GNRI should be used as a predictive indicator of adverse outcomes during malignancy treatment.

Background The impact of albumin-to-alkaline phosphatase ratio (AAPR) on prognosis in cancer patients remains uncertain, despite having multiple relevant studies in publication. Methods We systemically compiled literatures from 3 databases (Cochrane Library, PubMed, and Web of Science) updated to May 24th, 2020. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed and synthesized using STATA 14, values were then pooled and utilized in order to assess the overall impact of AAPR on patient’s prognosis. Results In total, 18 studies involving 25 cohorts with 7019 cases were incorporated. Pooled results originated from both univariate and multivariate analyses (HR = 2.14, 95%CI:1.83–2.51, random-effects model; HR = 1.93, 95%CI:1.75–2.12, fixed-effects model; respectively) suggested that decreased AAPR had adverse effect on overall survival (OS). Similarly, pooled results from both univariate and multivariate analysis of fixed-effects model, evinced that decreased AAPR also had adverse effect on disease-free survival (DFS) (HR = 1.81, 95%CI:1.60–2.04, I2 = 29.5%, P = 0.174; HR = 1.69, 95%CI:1.45–1.97, I2 = 13.0%, P = 0.330; respectively), progression-free survival (PFS) (HR = 1.71, 95%CI:1.31–2.22, I2 = 0.0%, P = 0.754; HR = 1.90, 95%CI:1.16–3.12, I2 = 0.0%, P = 0.339; respectively), and cancer-specific survival (CSS) (HR = 2.22, 95%CI:1.67–2.95, I2 = 5.6%, P = 0.347; HR = 1.88, 95%CI:1.38–2.57, I2 = 26.4%, P = 0.244; respectively). Admittedly, heterogeneity and publication bias existed, but stratification of univariate meta-analytic results, as well as adjusted meta-analytic results via trim and fill method, all showed that AAPR still significantly correlated with poor OS despite of confounding factors. Conclusions In summary, decreased AAPR had adverse effect on prognosis in cancer patients. As an inexpensive and convenient ratio derived from liver function test, AAPR might become a promising indicator of prognosis in human cancers.

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