Non-cancerous Patients Research Articles

Non-cancer febrile neutropenia in children: pathogens, antimicrobial susceptibilities, and outcomes

BackgroundFebrile neutropenia is a medical emergency and remains a significant cause of morbidity and mortality, it is defined as a temperature > 38.3 °C (101 °F), or a sustained temperature > 38.0 °C (100.4 °F) for more than 1 h in a neutropenic patient. Neutropenia is defined as a decrease in the absolute number of neutrophils in the blood < 1500 cells/ mm3 in children.Aim of the studyTo identify the specific pathogens causing infections, determine antimicrobial susceptibility, and identify factors associated with morbidity and mortality in febrile neutropenic children.MethodsA prospective cohort study, 38 non-cancerous pediatric patients admitted with 61 febrile episodes, was conducted. Sepsis screen, pan-cultures, and tests to identify the causative pathogens and antimicrobial sensitivity were collected.ResultsCoagulase-negative staphylococci (CONS) infection accounted for 38.4% of all positive cultures, while Klebsiella infection represented 23%. SARS-CoV2 (severe acute respiratory syndrome coronavirus 2) virus infection accounted for 23% of febrile episodes that lead to COVID-19 (coronavirus disease of 2019) sickness; however, it did not significantly impact patients’ outcomes. Unfavorable outcomes were associated with higher C-reactive protein (CRP) levels, positive blood cultures, and gram-negative organisms (p = < 0.001, 0.013, 0.038 respectively). Prolonged duration of fever and elevated CRP levels were significant predictors of poor outcomes in febrile neutropenia, with a sensitivity of 88.9% and 100% and specificity of 70.6% and 62.3%, respectively.ConclusionAmong febrile neutropenic patients, CONS is the most common pathogen, while Klebsiella is the most common gram-negative infection. Gram-positive organisms predominate in bloodstream infections. Prolonged duration of fever and elevated CRP levels can significantly predict poor outcomes.

Circ_0000592 facilitates the progression of esophageal squamous cell carcinoma via miR-155-5p/FZD5 axis.

Esophageal squamous cell carcinoma (ESCC) is one of the gastrointestinal malignancies with high prevalence and poor prognosis. Previous reports suggested that circular ribose nucleic acidsmight exert regulatory functions in ESCC. This study aims to explore the role of circ_0000592 in ESCC progression, providing novel insights into the diagnosis and therapeutic avenues for ESCC. The GSE131969 data set was utilized to assess circ_0000592 expression in ESCC. The validation was performed in the tumorous tissues of ESCC patients (n = 80) and human-immortalized ESCC cell lines. The correlation between circ_0000592 expression and prognosis was analyzed. The impact of circ_0000592 on ESCC cell activity was evaluated through downregulating circ_0000592, as well as encompassing cell viability, migration, and invasion abilities. The downstream pathway of circ_0000592 was explored by binding site prediction from the TargetScan database, followed by in vitro and in vivo experiments. An in vivo xenograft tumor model was established to highlight the role of circ_0000592 in ESCC. Patients with ESCC exhibited higher circ_0000592 expression levels compared to noncancerous patients, which were associated with reduced survival time, higher TNM stage, and increased lymph node metastasis. The circ_0000592 downregulation suppressed cell viability, migration, and invasion abilities in vitro. Mechanistically, circ_0000592 countered the inhibitory effects on the target gene Frizzled 5 (FZD5) through interactions with miR-155-5p. The overexpression of miR-155-5p curtailed the luciferase activity of circ_0000592 in ESCC cells, inhibiting downstream molecule FZD5 protein expression and subsequently mitigating the detrimental consequences of escalated circ_0000592 expression in ESCC cells. Consistently, circ_0000592 downregulation curbed proliferation and metastasis of ESCC tumors in vivo. In summary, circ_0000592 promoted the progress of ESCC by counteracting the inhibitory impact on FZD5 through its interaction with miR-155-5p. Together, our findings highlighted circ_0000592 as a prospective therapeutic target for ESCC.

Examination of the Hemoglobin, Albumin, Lymphocyte, and Platelet Score of Testicular Tumor: Comparison of Pre- and Postoperative and Non-Cancerous Patients

Examination of the Hemoglobin, Albumin, Lymphocyte, and Platelet Score of Testicular Tumor: Comparison of Pre- and Postoperative and Non-Cancerous Patients

Serum Insights: Leveraging the Power of miRNA Profiling as an Early Diagnostic Tool for Non-Small Cell Lung Cancer.

Non-small cell lung cancer is the predominant form of lung cancer and is associated with a poor prognosis. MiRNAs implicated in cancer initiation and progression can be easily detected in liquid biopsy samples and have the potential to serve as non-invasive biomarkers. In this study, we employed next-generation sequencing to globally profile miRNAs in serum samples from 71 early-stage NSCLC patients and 47 non-cancerous pulmonary condition patients. Preliminary analysis of differentially expressed miRNAs revealed 28 upregulated miRNAs in NSCLC compared to the control group. Functional enrichment analyses unveiled their involvement in NSCLC signaling pathways. Subsequently, we developed a gradient-boosting decision tree classifier based on 2588 miRNAs, which demonstrated high accuracy (0.837), sensitivity (0.806), and specificity (0.859) in effectively distinguishing NSCLC from non-cancerous individuals. Shapley Additive exPlanations analysis improved the model metrics by identifying the top 15 miRNAs with the strongest discriminatory value, yielding an AUC of 0.96 ± 0.04, accuracy of 0.896, sensitivity of 0.884, and specificity of 0.903. Our study establishes the potential utility of a non-invasive serum miRNA signature as a supportive tool for early detection of NSCLC while also shedding light on dysregulated miRNAs in NSCLC biology. For enhanced credibility and understanding, further validation in an independent cohort of patients is warranted.

Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis.

Gastric cancer is the second most prevalent and deadly cancer in China. Microbiota play an important role in gastric tumorigenesis. However, the available microbial marker studies for gastric cancer do not have consistent results. We searched PubMed for 16S rRNA sequencing in relevant literature on Chinese patients from 1 January 2005 to 18 July 2022, and 16 original articles were finally obtained. Alpha diversity, beta diversity, and bacterial taxa were used to explore the differences in gastric microbiota. Linear discriminant analysis of effect size and a random forest model were used to find the combination of genera with the best diagnostic efficacy. Streptococcus, Pseudomonas, Fusobacterium, Selenomonas, Peptostreptococcus, and Prevotella showed significant differences between gastric cancer and non-gastric cancer, but a single genus performed poorly in identifying patients with gastric cancer. However, a combination of genera Streptococcus, Peptostreptococcus, Selenomonas, Pseudomonas, and Prevotella had excellent performance in screening gastric cancer with the median area under the curve values of 0.7525 (range: 0.5859-0.9350), 0.8818 (range: 0.7397-0.9533), and 0.7435 (range: 0.7131-0.8483) in the Matched, Unmatched, and Other groups, respectively. Therefore, the results indicated that this combination of genera has good diagnostic efficacy and wide applicability for patients with gastric cancer, which may provide new clues for the non-invasive diagnosis of gastric cancer. IMPORTANCE Gastric cancer is a significant and growing health problem in China. Studies have revealed significant differences in gastric microbiota between patients with gastric cancer and non-cancerous patients, suggesting that microbiota may play a role in tumorigenesis. In this meta-analysis, existing 16S rRNA microbial data were analyzed to find combinations consisting of five genera, which had good efficacy in distinguishing gastric cancer from non-cancerous patients in multiple types of samples. These results lend support to the use of microbial markers in detecting gastric cancer. Moreover, these biomarkers are plausible candidates for further mechanistic research into the role of the microbiota in tumorigenesis.

Molecular Comparative Study of Virulence Factors Produced by Gram-Negative Bacteria Isolated from Several Cancer Cases and NonCancer Patients in Erbil Governorate, Iraq

Background and objectives: Gram-negative bacteria are one of the most prevalent complications among immunocompromised cancer sufferers and pose the greatest threat to these patients. Our study aimed to conduct research on Gram-negative bacteria isolated from various clinical samples among cancerous patients and non-cancerous patients in Erbil city to analyze and compare some virulence genes among them such as tuf, atpD1, atpD2, ms-1, ms-2 and ms-3. Methods: The current study was carried out in Nanakaly hospital and other public health hospitals in Erbil- Kurdistan region at a period extending from August 2021 to March 2022. A total of 100 different clinical samples including urine, sputum, wound swab, stool, blood, have been collected from patients with different types of cancer (n=50) and non-cancerous patients (n=50), from both gender (male and female), without limited age group. Gram-negative bacterial isolates identified by microscopical, macroscopical analysis and Vitek II compact system. Results: The results of amplification of tuf gene among the cancerous patients were (70%), while the results among the non-cancerous patients was (52%). The percentage of atpD1 from cancer patients were (52%), as well as the appearance among non-cancerous patients were (44%) isolates. The results of atpD2 among cancer patients were (52%). However, the average of atpD2 among patients without cancer were (48%). The results of agarose gel electrophoresis of amplicons appeared that (32%) samples possess ms-1 among cancer cases, while there have not any positive results for control patients. Also, the results of ms-2 gene were (28%) from cancer patients, whereas, the prevalence of ms-2 gene marker among patients without cancer was (6%). The distribution of ms-3 gene was (22%) among cancer patients. Otherwise, the prevalence from samples of patients other than cancer were (20%). According to the statistical tests, the results showed no significant association between genes and type of bacteria in cancerous patients as well as in non-cancerous patients. Conclusions: tuf, atpD1 and atpD2 genes sealed a discriminated gene as a virulence factor encoding genes for identification of gram-negative bacteria. To the public health and especially from patients with cancer there is a main distribution of ms-1, ms-2 and ms-3 genes among gram-negative bacteria.

EARLY DETECTION OF LUNGS CANCER USING MACHINE LEARNING ALGORITHMS

Medical healthcare systems store a large amount of clinical data about patients related to their biographies and disease information. Doctors use clinical data for the early detection of diseases that helps with proper patients’ treatments to save their lives. These clinical systems are helpful in detecting cancer diseases at early stages to save people's lives. Lung cancer is the third largely spreading disease in human beings all over the globe, which may lead so many people to death because of inaccurate detection of their disease at the initial stages. Therefore, this study will help doctors and radiologists in the detection of lung cancerous and non-cancerous patients at early stages with a random forest algorithm to save patients’ lives. In this research work, a new and novel model based on random forest algorithm was employed to detect lung cancer from the Wisconsin data set. Lung cancer was detected at early stages, and it was decided whether targeted patient was cancerous or non-cancerous. This experimental outcome showed that the proposed methodology achieved an accuracy rate that was batter compared to previous studies for early detection of lung cancer.

METABOLIC DISORDERS IN PATIENTS WITH ONCOLOGIC PATHOLOGY

Relevance: Metabolic disorders often take on a systemic character. It affects carbohydrate, lipid, and hormonal metabolism. Moreover,&#x0D; these changes promote the development and aggravation of several pathologies. The prevalence of metabolic disorders, including obesity,&#x0D; is increasing worldwide and in Kazakhstan.&#x0D; The study focused on the clinical characteristics of metabolic syndrome (MS) components in patients with cancer comorbidities.&#x0D; Methods: The materials included medical records of cancer patients with MS – 35 people (main group) and non-cancerous patients&#x0D; with MS – 35 people (control group). MS was diagnosed with a combination of three symptoms: abdominal obesity, high blood pressure,&#x0D; and increased high-density lipoprotein cholesterol (HDL-C) levels. The data were analyzed and processed using the STATIS-TICA 10&#x0D; software package. The significance criterion was p&lt;0.05.&#x0D; Results: All studied patients were diagnosed with abdominal obesity. Indicators analysis showed a significant difference in HDL-C&#x0D; concentration in the main and control groups: 3.8 mmol/L in cancer patients and 5.7 mmol/L in the controls. No significant difference in&#x0D; blood pressure was found.&#x0D; Conclusion: The age of patients with MS evidences a threatening tendency to develop metabolic disorders in young and middle ages.&#x0D; A significantly lower concentration of LDL-C in cancer patients compared with the controls allows using this parameter to predict cancer&#x0D; ]development in patients diagnosed with MS. Thus, HDL-C concentration could be used as a metabolic marker for pre-symptomatic&#x0D; diagnostics.

ABSTRACT METABOLIC DISORDERS IN PATIENTS WITH ONCOLOGIC PATHOLOGY

Relevance: Metabolic disorders often take on a systemic character. It affects carbohydrate, lipid, and hormonal metabolism. Moreover, these&#x0D; changes promote the development and aggravation of several pathologies. The prevalence of metabolic disorders, including obesity, is increasing&#x0D; world-wide and in Kazakhstan.&#x0D; The study focused on the clinical characteristics of metabolic syndrome (MS) components in pa-tients with cancer comorbidities.&#x0D; Methods: The materials included medical records of cancer patients with MS – 35 people (main group) and non-cancerous patients with&#x0D; MS – 35 people (control group). MS was diagnosed with a combination of three symptoms: abdominal obesity, high blood pressure, and increased high-density lipoprotein cholesterol (HDL-C) levels. The data were analyzed and processed using the STATIS-TICA 10 software package.&#x0D; The significance criterion was p&lt;0.05.&#x0D; Results: All studied patients were diagnosed with abdominal obesity. Indicators analysis showed a significant difference in HDL-C concentration in the main and control groups: 3.8 mmol/l in cancer patients and 5.7 mmol/l in the controls. No significant difference in blood pressure was&#x0D; found.&#x0D; Conclusion: The age of patients with MS evidences a threatening tendency to develop metabolic disorders in young and middle ages. A significantly lower concentration of LDL-C in cancer patients compared with the controls allows using this parameter to predict cancer ]development in&#x0D; patients diagnosed with MS. Thus, HDL-C concentration could be used as a metabolic marker for pre-symptomatic diagnostics.

Classifying Sarcoma Cancer Using Deep Neural Networks Based on Multi-Omics Data

The challenge in classifying cancer may lead to inaccurate classification of cancers, especially sarcoma cancer since it consists of rare types of cancer. It is hard for the clinician to confirm the patient's condition because an accurate diagnosis can only be made by the specialist pathology. Therefore, instead of a single omics is used to identify the disease marker, an approach of integrating these omics to represent multi-omics brings more advantages in detecting and presenting the phenotype of the cancers. Nowadays, the advancement of computational models especially deep learning offered promising approaches in solving high-level omics of data with faster processing speed. Hence, the purpose of this study is to classify cancer and non-cancerous patients using Stacked Denoising Autoencoder (SDAE) and One-dimensional Convolutional Neural Network (1D CNN) to evaluate which algorithm classifies better using high correlated multi-omics data. The study employed both computational models to fit multi-omics dataset. Sarcoma omics datasets used in this study was obtained from the Multi-Omics Cancer Benchmark TCGA Pre-processed Data of ACGT Ron Shamir Lab repository. From the results, the accuracy obtained for the SDAE was 50.93% and 52.78% for the 1D CNN. The result show 1D CNN model outperformed SDAE in classifying sarcoma cancer.

Clinical outcomes of COVID-19 patients with solid and hematological cancer: a meta-analysis and systematic review

Background: Previous research has consistently shown the significant difference in outcome between cancerous and non-cancerous patients with coronavirus disease 2019 (COVID-19). However, no studies have compared the clinical manifestation of COVID-19 in hematologic cancers patients and solid cancers patients. Therefore, we analyzed the outcome of COVID-19 patients with hematological cancer and primary solid cancer worldwide through a meta-analysis and systematic review. Methods: This meta-analysis and systematic review included English language articles published between December 2019 – January 2021 from Pubmed and Google Scholar. The Newcastle Ottawa Score was used to assess the quality and bias of included studies. The outcome measures were case-fatality rate and critical care events for COVID-19 patients with cancer and comorbidities. Results: The initial search found 8910 articles, of 20 were included in the analysis. Critical care events and mortality were higher in the hematological than primary solid cancer group (relative risk (RR)=1.22 &amp; 1.65; p &lt;0.001). Conversely, mortality was lower in patients with two or fewer comorbidities (RR=0.57; p&lt;0.001) and patients under the 75-year-old group (RR=0.53; p&lt; 0.05). Conclusions: Hematologic malignancy, age, and the number of comorbidities are predictor factors for worse prognosis in COVID-19 infection.

Ethics and Law.

Ethics and Law.

Characterization and Functional Prediction of Bacteria in Ovarian Tissues.

The theory of a "sterile" female upper reproductive tract has been encountering increasing opposition due to advancements in bacterial detection. However, whether ovaries contain bacteria has not yet been confirmed yet. Herein, an experiment to detect bacteria in ovarian tissues was introduced. We chose ovarian cancer patients in the cancer group and noncancerous patients in the control group. 16S rRNA gene sequencing was used to differentiate bacteria in ovarian tissues from the cancer and control groups. Furthermore, we predicted the functional composition of the identified bacteria by using BugBase and PICRUSt. This method can also be used in other viscera and tissues since many organs have been proven to harbor bacteria in recent years. The presence of bacteria in viscera and tissues may help scientists evaluate cancerous and normal tissues and may be aid in the treatment of cancer.

COVID-19 amongst cancer patients: An experience from Oman.

To evaluate the extent of coronavirus infection in cancer patients along with their demographics, laboratory findings and outcomes in a tertiary care setting. The study was conducted in Muscat, Oman, from March 24 to October 23, 2020. The data was collected from the cancer registry of the Directorate-General of Non-Communicable Diseases, Ministry of Health, Oman. Data of inpatient coronavirus cases were retrieved from the electronic medical records system of the Royal Hospital, Muscat, all tertiary hospitals linked electronically to the registry and the coronavirus registry of Oman. The data of cancer patients infected with coronavirus was analysed and compared with non-cancer coronavirus-infected patients. Data was analysed using IBM SPSS 2019 v26. Of the 16,260 cancer patients, 77(0.47%) were infected with COVID-19 compared to 111,837(2.17%) in the national population. Mortality among cancer patients with COVID-19 was high 27(35.1%) compared to 1,147(1.03%) in the national population. Cancer patients with COVID-19 also had diabetes 15(20%), hypertension 20(26%), renal complications 15(20%) and cardiac issues 9(12%). Of the total, 32(41.6%) cancer patients with COVID-19 had received active cancer treatment within the preceding 4 weeks. The data on coronavirus infection outcome is emerging at a rapid pace focussing on the impact of underlying diseases, and the capacity of healthcare systems. Oncologists should customise cancer management, while cancer patients must practise social distancing, and seek prompt evaluation of suspicious symptoms.

Effect of Chemo-radiotherapy on Salivary Flora of Oral Cancer Patients

Management of cancers of oral cancers has remained a major challenge in India and globally. Radiotherapy and chemotherapy are mostly employed for treatment which inflicts changes in oral mucosa and makes it vulnerable for bacterial colonization and eventual infections. This study aims at evaluating the changes in oropharyngeal flora (bacteria and yeast) in oral cancer patients treated by a combination of chemo-radiotherapy with the control groups comprising of non-cancerous patients living in the same environment. This prospective evaluation included Seventy-seven patients with oral squamous cell carcinomas in the study group. Whereas the control group comprised of twenty-five non-cancerous patients. Saliva samples were collected from patients with oral carcinomas and those of the control group for bacteriological examination, and were transported within 2 hours to the laboratory and immediately inoculated and incubated. The oral microflora samples collected were evaluated for the presence of bacteria in saliva in both study and control group of patients. We evaluated the change in salivary oral flora during chemo-radiotherapy treatment. A statistically significant increase in growth of normal as well as abnormal oral flora was observed post-radiation. Escherichia coli showed a significant decrease in post-RT and also near to significant in control. Various changes in salivary oral flora were observed during the course of chemo-radiotherapy in study and controls groups. This shows that there are some sensitive spots in the oral cavity where the occurrence of oral cancer is more.

P-246 Comparison of microbiome diversity in gastric cancer patients and in non-cancerous patients

Gastric cancer is the fifth most common cancer worldwide and it is the most commonly diagnosed cancer in Korea. The most clearly known microbiologic risk factor is Heliobacter pylori infection. H.pylori-induced gastritis reduces acid secretion from gastric mucosa and causes atrophic gastritis and intestinal metaplasia, which are known to be pre-cancerous lesions. According to previous studies, H.pylori is rarely detected in atrophic mucosa or in mucosa with intestinal metaplasia. This suggests that the hypochlorhydric conditions created by H.pylori provide a suitable environment for carcinogenesis, rather than H.pylori working as the direct carcinogen itself. This raises the possibility that bacteria other than H.pylori could contribute to carcinogenesis of gastric cancer. The aim of the present study was to compare the composition of the gastric microbiome of advanced gastric cancer patients and non-cancerous individuals. Gastric mucosa collected by biopsy during esophagogastroduodenoscopy (EGD) from seven patients with advanced gastric cancer (AGC) and six non-cancerous patients (control group) was evaluated. Gastric biopsies were obtained from the margin of cancer in cancer patients. In the control group, biopsies were done from antrum with normal mucosal morphology. DNA was extracted from the gastric mucosal tissues and 16s rRNA genes were amplified from the isolated DNA. Then they were analyzed using the molecular profiling approach terminal restriction fragment length polymorphism (T-RFLP). Cloning and sequencing of 16S rRNA genes was performed to discover the identities of bacteria residing in the gastric mucosa. A higher number of species were detected in the control group, with an average of 102 species, compared to the cancer group, with an average of 72 species. The gastric cancer microbiome was characterized by reduced microbial diversity compared to that of the control group. Many different bacterial species were found in both groups but distribution was quite different between the two groups. Fusobacteria was more dominant in the cancer group and Rhodobacterales was found more prominent in the control group. Gastric H.pylori was detected only in one patient from each group. A more diverse gastric microbiome was observed in non-cancerous patients and the composition of species was different between the two groups. These results suggest that microbial dysbiosis may be involved in gastric carcinogenesis, but it is not yet clear that microbial transition accelerates carcinogenesis. Further studies should include a more detailed analysis of the spatial and temporal composition of the gastric microbiome. A better understanding of microbial differences and changes in healthy and gastric cancer patients could verify the carcinogenesis of gastric cancer.

COVID-19 Risk Factors for Cancer Patients: A First Report with Comparator Data from COVID-19 Negative Cancer Patients.

Simple SummaryThe COVID-19 pandemic has had a detrimental impact on cancer patients globally. Whilst there are several studies looking at the potential risk factors for COVID-19 disease and related death, most of these include non-cancerous patients as the COVID-19 negative comparator group, meaning it is difficult to draw hard conclusions as to the implications for cancer patients. In our study, we utilized data from over 2000 cancer patients from a large tertiary Cancer Centre in London. In summary, our study found that patients who are male, of Black or Asian ethnicity, or with a hematological malignancy are at an increased risk of COVID-19. The use of cancer patients as the COVID-19 negative comparator group is a major advantage to the study as it means we can better understand the true impact of COVID-19 on cancer patients and identify which factors pose the biggest risk to their likelihood of infection with SARS-CoV2.Very few studies investigating COVID-19 in cancer patients have included cancer patients as controls. We aimed to identify factors associated with the risk of testing positive for SARS CoV2 infection in a cohort of cancer patients. We analyzed data from all cancer patients swabbed for COVID-19 between 1st March and 31st July 2020 at Guy’s Cancer Centre. We conducted logistic regression analyses to identify which factors were associated with a positive COVID-19 test. Results: Of the 2152 patients tested for COVID-19, 190 (9%) tested positive. Male sex, black ethnicity, and hematological cancer type were positively associated with risk of COVID-19 (OR = 1.85, 95%CI:1.37–2.51; OR = 1.93, 95%CI:1.31–2.84; OR = 2.29, 95%CI:1.45–3.62, respectively) as compared to females, white ethnicity, or solid cancer type, respectively. Male, Asian ethnicity, and hematological cancer type were associated with an increased risk of severe COVID-19 (OR = 3.12, 95%CI:1.58–6.14; OR = 2.97, 95%CI:1.00–8.93; OR = 2.43, 95%CI:1.00–5.90, respectively). This study is one of the first to compare the risk of COVID-19 incidence and severity in cancer patients when including cancer patients as controls. Results from this study have echoed those of previous reports, that patients who are male, of black or Asian ethnicity, or with a hematological malignancy are at an increased risk of COVID-19.

Immunological alternation in COVID-19 patients with cancer and its implications on mortality

ABSTRACT Patients with malignancy were reportedly more susceptible and vulnerable to Coronavirus Disease 2019 (COVID-19), and witnessed a greater mortality risk in COVID-19 infection than noncancerous patients. But the role of immune dysregulation of malignant patients on poor prognosis of COVID-19 has remained insufficiently investigated. Here we conducted a retrospective cohort study that included 2,052 patients hospitalized with COVID-19 (Cancer, n = 93; Non-cancer, n = 1,959), and compared the immunological characteristics of both cohorts. We used stratification analysis, multivariate regressions, and propensity-score matching to evaluate the effect of immunological indices. In result, COVID-19 patients with cancer had ongoing and significantly elevated inflammatory factors and cytokines (high-sensitivity C-reactive protein, procalcitonin, interleukin (IL)-2 receptor, IL-6, IL-8), as well as decreased immune cells (CD8 + T cells, CD4 + T cells, B cells, NK cells, Th and Ts cells) than those without cancer. The mortality rate was significantly higher in cancer cohort (24.7%) than non-cancer cohort (10.8%). By stratification analysis, COVID-19 patients with immune dysregulation had poorer prognosis than those with the relatively normal immune system both in cancer and non-cancer cohort. By logistic regression, Cox regression, and propensity-score matching, we found that prior to adjustment for immunological indices, cancer history was associated with an increased mortality risk of COVID-19 (p < .05); after adjustment for immunological indices, cancer history was no longer an independent risk factor for poor prognosis of COVID-19 (p > .30). In conclusion, COVID-19 patients with cancer had more severely dysregulated immune responses than noncancerous patients, which might account for their poorer prognosis. Clinical Trial: This study has been registered on the Chinese Clinical Trial Registry (No. ChiCTR2000032161).

Effect of Body Mass Index on Serum CA125 Level in Females with PCOS

CA125 is a glycoprotein mucins (MUC16) tumor marker, used in screening, ovarian and endometrial malignancies and in monitoring therapy, early recurrences, and prognosis of these cancers. Hormonal induction for ovulation can elevate the risk of ovarian cancers so CA125 may be used for screening in PCOS as an unsafe group and the way of treatment may need to be changed in these patients. Polycystic Ovarian Syndrome (PCOS) is one of the most common hormonal disturbed diseases that can affect females in reproductive life. It has both metabolic and fertility impacts that can be seen in the reproductive period and post-menopausal life. To study the correlation between PCOS and CA125 level in relation to body weight in non-cancerous patients. 60 women were selected with age 18-42-year-old forty of them were diagnosed with PCOS according to Rotterdam criteria. They were divided into two groups according to BMI G1 was more than 25 kg/m2 (overweight and obese) G2 was less than 25 kg/m2 (normal) and the G3 was 20 healthy non-PCOS BMI less than 25 kg/m2. Blood samples were taken in the early follicular phase for assessing luteinizing hormone (LH), follicular stimulating hormone (FSH) and, free testosterone (FT) hormone. Other blood samples were taken at the late follicular phase to measure CA125 levels using Enzyme-Linked Immune Sorbent Assay (ELISA). PCOS G2 were significantly higher in the concentration of CA125 than PCOS G1 (p&lt; 0.05), but there was no significant difference in CA125 level in groups when there is no significant difference in body mass index (BMI) between PCOS G1 and G2. P&gt;0.05. The negative relation between CA125 concentration and weight. The tumor marker CA125 efficacy is decreased in obese women. Furthermore, PCOS not causes an increase in CA125 in the non-cancerous patient.

Clinical characteristics, outcomes, and risk factors for mortality in hospitalized patients with COVID-19 and cancer history: a propensity score-matched study

BackgroundCOVID-19 has caused great concern for patients with underlying medical conditions. We aimed to determine the prognosis of patients with current or previous cancer with either a PCR-confirmed COVID-19 infection or a probable diagnosis according to chest CT scan.MethodsWe conducted a case control study in a referral hospital on confirmed COVID-19 adult patients with and without a history of cancer from February25th to April21st, 2020. Patients were matched according to age, gender, and underlying diseases including ischemic heart disease (IHD), diabetes mellitus (DM), and hypertension (HTN). Demographic features, clinical data, comorbidities, symptoms, vital signs, laboratory findings, and chest computed tomography (CT) images have been extracted from patients’ medical records. Multivariable logistic regression was used to estimate odd ratios and 95% confidence intervals of each factor of interest with outcomes.ResultsFifty-three confirmed COVID-19 patients with history of cancer were recruited and compared with 106 non-cancerous COVID-19 patients as controls. Male to female ratio was 1.33 and 45% were older than 65. Dyspnea and fever were the most common presenting symptoms in our population with 57.86 and 52.83% respectively. Moreover, dyspnea was significantly associated with an increased rate of mortality in the cancer subgroup (p = 0.013). Twenty-six patients (49%) survived among the cancer group while 89 patients (84%) survived in control (p = 0.000). in cancer group, patients with hematologic cancer had 63% mortality while patients with solid tumors had 37%. multivariate analysis model for survival prediction showed that history of cancer, impaired consciousness level, tachypnea, tachycardia, leukocytosis and thrombocytopenia were associated with an increased risk of death.ConclusionIn our study, cancer increased the mortality rate and hospital stay of COVID-19 patients and this effect remains significant after adjustment of confounders. Compared to solid tumors, hematologic malignancies have been associated with worse consequences and higher mortality rate. Clinical and para-clinical indicators were not appropriate to predict death in these patients.