Prediction of early-wheelchair dependence in multiple system atrophy based on machine learning algorithm: A prospective cohort study

Objective

The predictive factors for wheelchair dependence in patients with multiple system atrophy (MSA) are unclear. We aimed to explore the predictive factors for early-wheelchair dependence in patients with MSA focusing on clinical features and blood biomarkers.

Methods

This is a prospective cohort study. This study included patients diagnosed with MSA between January 2014 and December 2019. At the deadline of October 2021, patients met the diagnosis of probable MSA were included in the analysis. Random forest (RF) was used to establish a predictive model for early-wheelchair dependence. Accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the model.

Results

Altogether, 100 patients with MSA including 49 with wheelchair dependence and 51 without wheelchair dependence were enrolled in the RF model. Baseline plasma neurofilament light chain (NFL) levels were higher in patients with wheelchair dependence than in those without (P = 0.037). According to the Gini index, the five major predictive factors were disease duration, age of onset, Unified MSA Rating Scale (UMSARS)-II score, NFL, and UMSARS-I score, followed by C-reactive protein (CRP) levels, neutrophil-to-lymphocyte ratio (NLR), UMSARS-IV score, symptom onset, orthostatic hypotension, sex, urinary incontinence, and diagnosis subtype. The sensitivity, specificity, accuracy, and AUC of the RF model were 70.82 %, 74.55 %, 72.29 %, and 0.72, respectively.

Conclusion

Besides clinical features, baseline features including NFL, CRP, and NLR were potential predictive biomarkers of early-wheelchair dependence in MSA. These findings provide new insights into the trials regarding early intervention in MSA.

Plasma-induced nanoparticle aggregation for stratifying COVID-19 patients according to disease severity

Stratifying patients according to disease severity has been a major hurdle during the COVID-19 pandemic. This usually requires evaluating the levels of several biomarkers, which may be cumbersome when rapid decisions are required. In this manuscript we show that a single nanoparticle aggregation test can be used to distinguish patients that require intensive care from those that have already been discharged from the intensive care unit (ICU). It consists of diluting a platelet-free plasma sample and then adding gold nanoparticles. The nanoparticles aggregate to a larger extent when the samples are obtained from a patient in the ICU. This changes the color of the colloidal suspension, which can be evaluated by measuring the pixel intensity of a photograph. Although the exact factor or combination of factors behind the different aggregation behavior is unknown, control experiments demonstrate that the presence of proteins in the samples is crucial for the test to work. Principal component analysis demonstrates that the test result is highly correlated to biomarkers of prognosis and inflammation that are commonly used to evaluate the severity of COVID-19 patients. The results shown here pave the way to develop nanoparticle aggregation assays that classify COVID-19 patients according to disease severity, which could be useful to de-escalate care safely and make a better use of hospital resources.

Absolute lymphocyte count as a predictor of mortality and readmission in heart failure hospitalization

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Lymphopenia (<1500/mm³) was associated with 82% higher mortality in heart failure patients irrespective of ejection fraction.

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Lymphopenia was a good predictor of all-cause readmission in heart failure patients with reduced ejection fraction.

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Due to cost-effectiveness, easy availability, and ability to predict outcomes in the short-term and medium-term, lymphopenia can be a valuable tool in the mortality, readmission prediction model of heart failure.

Background

There is renewed interest in pursuing frugal and readily available laboratory markers to predict mortality and readmission in heart failure. We aim to determine the relationship between absolute lymphocyte count (ALC) and clinical outcomes in patients with heart failure hospitalization.

Methods

This was a retrospective cohort study of patients with heart failure. Patients were divided into two groups based on ALC, less than or equal to 1500 cells/mm3 and > 1500 cells/ mm3. The primary outcome was all-cause mortality. We did subgroup analysis based on ejection fraction and studied the association between ALC categories and clinical outcomes. Both ALC groups are matched by propensity score, outcomes were analyzed by Cox regression, and estimates are presented in hazard ratios (HR) and 95% confidence intervals (CI).

Results

We included 1029 patients in the pre-matched cohort and 766 patients in the propensity-score matched cohort. The median age was 64 years (IQR, 54–75), and 60.78% were male. In the matched cohort, ALC less than or equal to 1500 cells/mm3 had a higher risk of mortality compared with ALC > 1500 cells/mm3 (HR 1.51, 95% CI: 1.17–1.95; P = 0.002). These results were reproducible in subgroups of heart failure. When ALC was divided into four groups based on their levels, the lowest group of ALC had the highest risk of mortality.

Conclusions

In patients with heart failure and both subgroups, ALC less than or equal to 1500 cells/mm3 had a higher risk of mortality. Patients in lower groups of the ALC categories had a higher risk of mortality.

Complete remission of advanced lung adenocarcinoma with first-line pembrolizumab monotherapy: Two case reports

Immune checkpoint inhibitors (ICIs) are clinically used for treating advanced lung cancer, and some patients have achieved complete remission (CR) with ICI therapy in clinical trials. However, reports summarizing the clinical courses of such patients are limited. We report two cases of lung adenocarcinoma in which CR was achieved with first-line pembrolizumab monotherapy, and the therapeutic effect was maintained after treatment completion. Specific patients can achieve CR, even those who do not meet the previously reported predictors of treatment response other than high programmed death-ligand 1 expression. Thus, biomarkers that can accurately predict the clinical efficacy of ICIs are warranted.

Proinflammatory cytokines predict the incidence of diabetic peripheral neuropathy over 5 years in Chinese type 2 diabetes patients: A prospective cohort study

BACKGROUND

Inflammation has been implicated in the pathogenesis of diabetic peripheral neuropathy (DPN) as suggested in various cross-sectional studies. However, more convincing prospective studies in diabetes patients are scarce. Therefore, we aimed to evaluate whether proinflammatory cytokines could predict the incidence of DPN through a prospective study with a five-year follow-up.

METHODS

We followed up 315 patients with diabetes who did not have DPN, recruited from five community health centers in Shanghai in 2014, for an average of 5.06 years. Based on the integrity of blood samples, 106 patients were selected to obtain the proinflammatory cytokines. Plasma markers of proinflammatory cytokines at baseline included interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), vascular endothelial growth factor (VEGF), and intercellular adhesion molecule 1 (ICAM-1). Neuropathy was assessed by MSNI at baseline and during follow-up.

FINDINGS

Among the 106 chosen patients, 63 developed DPN after 5.06±1.14 years of follow-up. The baseline plasma levels of TNF-α, IL-6, and ICAM-1 were higher in the neuropathic group (p<0.05). In multivariate models, increased plasma levels of TNF-α (hazard ratio, HR: 8.74 [95% confidence interval, CI: 1.05-72.68]; p <0.05) and ICAM-1 (HR 23.74 [95% CI:1.47-383.81]; p<0.05) were both associated with incident DPN, after adjusting for known DPN risk factors.

INTERPRETATION

Increased plasma levels of proinflammatory factors, especially TNF-α and ICAM-1, predicted the incidence of DPN over 5 years in Chinese diabetes patients, but larger longitudinal studies are required for confirmation.

FUNDING

National Natural Science Foundation of China, Shanghai Talent Development Fund Program, Shanghai Shenkang Hospital Developing Center Clinical Scientific and Technological Innovation Program, Shanghai Science and Technology Committee Program, Shanghai General Hospital Program of Chinese traditional and Western medicine combination and Shanghai Municipal Commission of Health and Family Planning Clinical Research Project.

Characterization of Immune Checkpoint Inhibitor-Related Cardiotoxicity in Lung Cancer Patients From a Rural Setting

BACKGROUND

Immune checkpoint inhibitor (ICI)-related cardiotoxicity (iRC) is uncommon but can be fatal. There have been few reports of iRC from a rural cancer population and few data for iRC and inflammatory biomarkers.

OBJECTIVES

The purpose of this study was to characterize major adverse cardiac events (MACE) in ICI-treated lung cancer patients based in a rural setting and to assess the utility of C-reactive protein (CRP) and neutrophil-lymphocyte ratio (NLR) in the diagnosis of iRC.

METHODS

Patients with lung cancer treated with ICIs at Vidant Medical Center/East Carolina University (VMC/ECU) between 2015 and 2018 were retrospectively identified. MACE included myocarditis, non-ST-segment elevated myocardial infarction (NSTEMI), supraventricular tachycardia (SVT), and pericardial disorders. Medical history, laboratory values, pre-ICI electrocardiography (ECG), and echocardiography results were compared in patients with and without MACE.

RESULTS

Among 196 ICI-treated patients, 23 patients (11%) developed MACE at a median of 46 days from the first ICI infusion (interquartile range [IQR]: 17 to 83 days). Patients who developed MACE experienced myocarditis (n = 9), NSTEMI (n = 3), SVT (n = 7), and pericardial disorders (n = 4). Ejection fraction was not significantly different at the time of MACE compared to that at baseline (p = 0.495). Compared to baseline values, NLR (10.9 ± 8.3 vs. 20.7 ± 4.2, respectively; p = 0.032) and CRP (42.1 ± 10.1 mg/l vs. 109.9 ± 15.6 mg/l, respectively; p = 0.010) were significantly elevated at the time of MACE.

CONCLUSIONS

NLR and CRP were significantly elevated at the time of MACE compared to baseline values in ICI-treated patients. Larger datasets are needed to validate these findings and identify predictors of MACE that can be used in the diagnosis and management of ICI-related iRC.

Anemia, leukocytosis and thrombocytosis as prognostic factors in patients with cervical cancer treated with radical chemoradiotherapy: A retrospective cohort study

Introduction

Anemia has long been associated with poor prognosis in patients with cervical cancer. Recently, additional hematologic parameters have emerged as potential indicators of worse outcome in this patient group. In a cohort of cervical cancer patients treated with chemoradiotherapy (CRT) and brachytherapy, we report on the prognostic significance of hematologic parameters including anemia, leukocytosis, neutrophil to lymphocyte ratio (NLR), and thrombocytosis, the effect of combining anemia with other hematologic parameters, and the effect of changes in hemoglobin levels during treatment.

Materials and methods

Two-hundred fifty-seven cervical cancer patients were retrospectively identified from a single cancer institution’s database. Hematologic parameters were categorized as: anemia (hemoglobin ≤115 g/L), leukocytosis (white blood cell count >10 × 10⁹/L), thrombocytosis (platelets >400 × 10⁹/L), and NLR (ratio >5). The association between clinical factors and hematologic parameters on progression-free survival (PFS) and overall survival (OS) were assessed at 5 years.

Results

At 5 years, both pre-treatment anemia (PFS: 60% vs 34%, p < 0.0001; OS: 68% vs 41%, p < 0.0001) and on-treatment anemia (PFS: 62% vs 40%, p < 0.0001; OS: 70% vs 48%, p < 0.0001) were significantly associated with worse survival. This adverse effect on 5-year PFS and OS was increased in patients with both pre-treatment anemia and leukocytosis (PFS: 72% vs 42%, p < 0.0001; OS: 68% vs 37%, p < 0.0001) and pre-treatment anemia and elevated NLR (PFS: 61% vs 30%, p < 0.0001; OS: 68% vs 37%, p < 0.0001). Five-year PFS (50% vs 31%) and OS (60% vs 36%) was better in patients whose pre-treatment anemia improved to normal hemoglobin levels on treatment vs those patients who were anemic both pre- and on-treatment.

Conclusion

Pre-treatment and on-treatment anemia were significant, independent predictors of worse PFS and OS. Anemia and other hematologic parameters remain prognostic markers for cervical cancer patients. Improvement in PFS and OS was seen in patients with normalization of hemoglobin.

Effects of yogurt containing Lactobacillus plantarum HOKKAIDO on immune function and stress markers

Lactobacillus plantarum HOKKAIDO (HOKKAIDO strain) was isolated from well-pickled vegetables in Hokkaido, Japan. We report a randomized, double-blind, placebo-controlled study evaluating the effects of L. plantarum HOKKAIDO on immune function and stress markers in 171 adult subjects. Subjects were divided into three groups: the L. plantarum HOKKAIDO yogurt group, the placebo-1 group who ingested yogurt without the HOKKAIDO strain, and the placebo-2 group who ingested a yogurt-like dessert without the HOKKAIDO strain. Hematological tests and body composition measurements were performed before and after 4 and 8 weeks of blinded ingestion. Although no significant differences in natural killer cell activity were observed, it was found that neutrophil ratio significantly decreased and lymphocytes tended to increase in the HOKKAIDO strain yogurt group compared with the yogurt-like dessert group. In addition, the neutrophil-to-lymphocyte ratio, a stress marker, tended to improve in the HOKKAIDO strain yogurt group compared with the yogurt-like dessert group. These results suggest that the ingestion of HOKKAIDO strain yogurt tends to improve immune activity and decrease stress markers.

Pre-operative lymphocyte-to-monocyte ratio as a predictor of overall survival in patients suffering from osteosarcoma

Inflammatory markers have been proposed to predict clinical outcomes in many types of cancers. The purpose of this study was to explore the influence of the lymphocyte-to-monocyte ratio (LMR) on clinical prognosis of patients with osteosarcoma. This study collected 327 patients who underwent surgical treatment for osteosarcoma during the period 2006-2010. LMR was calculated from pre-operative peripheral blood cells counts. The optimal cut-off value of LMR was determined based on receiver operating characteristic curve analysis. Overall survival (OS) and event free survival (EFS) was plotted using the Kaplan-Meier method and evaluated by the log-rank test. A predictive model was established to predict clinical prognosis for OS, and the predictive accuracy of this model was determined by concordance index (c-index). Our results showed that young age, elevated alkaline phosphatase, metastasis at diagnosis, chemotherapy, lymphocyte and monocyte counts were significantly associated with LMR. Low LMR was associated with shorter OS and EFS (P < 0.001), and was an independent predictor of both OS and EFS (HR = 1.72, 95% CI = 1.14-2.60, P = 0.010; HR = 1.89, 95% CI = 1.32-2.57, P = 0.009). The nomogram performed well in the prediction of overall survival in patients with osteosarcoma (c-index 0.630). In conclusion, low pre-operative LMR is associated with a poor prognosis in patients suffering from osteosarcoma. A prospective study is warranted for further validation of our results.

Prognostic value of neutrophil-to-lymphocyte ratio in breast cancer

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A literature search was conducted using PubMed, Web of Science and CNKI.

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Increased NLR was a strong predictor for overall survival and disease-free survival.

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Subgroup analyses stratified by ethnicity, analysis method and metastasis were conducted.

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NLR could be considered as a predictive factor for patients with breast cancer.

Inflammation is an essential component of pathogenesis and progression of cancer. A high neutrophil-to-lymphocyte ratio (NLR) is considered as a prognostic indicator for breast cancer. This meta-analysis was conducted to establish the overall accuracy of the NLR test in the diagnosis of breast cancer. A comprehensive search of the literature was conducted by using PubMed, Web of Science and China National Knowledge Infrastructure (CNKI). Published studies dating up to July 2014 and 4,293 patients were enrolled in the present study. In order to evaluate the association between NLR and overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS) or cancer specific survival (CSS), the hazard ratios (HRs) and their 95% confidence intervals (CIs) were extracted. OS was the primary outcome. The results suggested that increased NLR was a strong predictor for OS with HR of 2.28 (95% CI = 1.08–4.80, P_{heterogeneity} < 0.001). Stratified analyses indicated that a high NLR appeared to be a negative prognostic marker in Caucasian populations (HR = 4.53, 95% CI = 3.11–6.60, P_{heterogeneity} = 0.096), multivariate analysis method (HR = 2.10, 95% CI = 1.52–2.89, P_{heterogeneity} = 0.591), and mixed metastasis (HR = 4.53, 95% CI = 3.11–6.60, P_{heterogeneity} = 0.096). Elevated NLR was associated with a high risk for DFS (HR = 1.38, 95% CI = 1.09–1.74, P_{heterogeneity} = 0.050) and in subgroups of multivariate analysis (HR = 1.64, 95% CI = 1.25–2.14, P_{heterogeneity} = 0.545) and mixed metastasis (HR = 1.99, 95% CI = 1.28–3.09, P_{heterogeneity} = 0.992). In summary, NLR could be considered as a predictive factor for patients with breast cancer.