title stringlengths 1 1.19k | keywords stringlengths 0 668 | concept stringlengths 0 909 | paragraph stringlengths 0 61.8k | PMID stringlengths 10 11 |
|---|---|---|---|---|
Conclusions | T2DM | INSULIN RESISTANCE | FMT with or without metformin significantly improve insulin resistance and body mass index and gut microbial communities of T2DM patients by colonization of donor-derived microbiota. | PMC9872724 |
Introduction | metabolic disease, T2DM, fasting blood glucose, postprandial blood glucose | TYPE 2 DIABETES MELLITUS, METABOLIC DISEASE, SECONDARY, HIGH INSULIN, INSULIN SENSITIVITY | Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by a decrease in pancreatic β-cell mass and function, and represents a failure to compensate for the high insulin demand of homeostatic model assessment of insulin resistant (HOMA-IR) states (The human intestines harbor a complex community of intestinal bacteria (We proposed that FMT would alter T2DM patients’ microbial ecology and thereafter improve the blood glucose and insulin sensitivity. An FMT clinical trial for the intervention of T2DM patients with metformin, FMT alone, and FMT plus metformin was initiated. The primary outcome was the evaluation of changes in insulin sensitivity (HOMA-IR and HOMA-HBCI), postprandial blood glucose (PBG), fasting blood glucose (FBG), hemoglobin A1c (HbA1c), and BMI between baseline and after 4 weeks of intervention. The secondary outcomes were the proportion of subjects acquiring least 20% of microbiota from the donor after FMT at week 4. | PMC9872724 |
Materials and methods | PMC9872724 | |||
Study population | gastrointestinal diseases, chronic infectious diseases, liver and kidney insufficiency, allergies, diabetic, Diabetes, cardiovascular and cerebrovascular diseases, 6)Leukopenia, T2DM | GASTROINTESTINAL DISEASES, VIRUS, HEART INSUFFICIENCY, ALLERGIES, HEPATITIS C, DIABETES, DISEASES, COMPLICATIONS | We recruited 29 adult T2DM patients, following the diagnostic criteria of the American Diabetes Association (ADA) for T2DM in 2019. We obtained written informed consent from all patients before screening. All patients volunteered to participate in the trial and exhibited good compliance and did not replace diabetic drugs in the study cycle. Patients were excluded if they had other diagnoses: 1) acute and chronic infectious diseases, gastrointestinal diseases, severe heart insufficiency, severe liver and kidney insufficiency, and/or other diseases or complications; 2) other gastrointestinal diseases that may affect drug absorption; 3) pregnant and lactating women; 4) people with allergies; 5) patients who have used other hormone therapy within the past three months; 6)Leukopenia or abnormal granulocytes; 7) cardiovascular and cerebrovascular diseases that first occurred in the past three months; 8) Participants in other clinical trials during the same period; 9) a history of human immunodeficiency virus (HIV) seropositivity after laboratory screening; and 10) hepatitis B virus surface antigen (HBsAg) positive or hepatitis C virus antibody (HCV-Ab) history after laboratory screening. During this period, the research team instructed all participants to maintain their original eating habits before and after the intervention, including total calories, types, diet culture, etc., and to maintain light to moderate physical activity (the same intensity) and avoid heavy physical activity. The study has been approved by the Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College Ethics Committee in Shantou, China(Ethics number:LHLL2019001), and was registered at Chinses Clinical Trial Registry.(Registration number: ChiCTR1900024636).( | PMC9872724 |
Research plan and outcomes | T2DM | SECONDARY, INSULIN RESISTANCE | This study used FMT as an auxiliary method to compare the therapeutic effects of solely metformin, solely FMT and FMT combined with metformin onT2DM patients. Eight T2DM patients received FMT plus metformin treatment, 9 patients underwent FMT alone and 12 patients received solely metformin treatment. The primary research objective was to evaluate the efficacy of FMT in assisting the metformin treatment in T2DM adult patients from the aspects of blood sugar control and insulin resistance. The secondary research objective was to observe the influence of FMT on the bacterial engraftment from donor microbiota during baseline inspection and week 4 intervention. We classified microbiota species identified in the recipients into four types and mainly focused on the donor-associated species as previously defined ( | PMC9872724 |
Intervention procedures | Screening of study donors was based on previous reports ( | PMC9872724 | ||
Fecal microbiota analysis by metagenomic sequencing | T2DM | Fecal samples from donor and T2DM patients were collected on the day of the medical examination and immediately frozen at −80°C. Fecal genomic DNA was extracted using the QIAamp Fast DNA Stool Mini Kit (Qiagen, CA, USA). DNA samples were stored at −20°C before use as templates for next-generation sequencing library preparation. Samples were fragmented to an average insert size of 400 bp and sequenced by Illumina Nova seq with PE 150 reagents. Reads were trimmed using KneadData with default parameters to filter the sequencing adapter, low-quality reads, and the human genome. The taxonomic composition was processed using kraken2 ( | PMC9872724 | |
Statistical analysis | Microbiota alpha diversity Shannon and Chao1 were calculated using the R program package ‘vegan’ (version 2.5.6). β-diversity metrics were obtained with rda and PERMANOVA with the adonis function. Principal Components analysis (PCA) was performed using the package vegan. Different analysis was performed to identify taxa with differentiating abundance in the different groups ( | PMC9872724 | ||
Results | PMC9872724 | |||
Characteristics of the study population | T2DM | A total of 36 patients with T2DM were assessed for eligibility, of whom 31 were recruited and randomized to either FMT plus metformin, FMT alone, or metformin from July 2019 to Oct 2021. One of participants in both FMT plus metformin and FMT alone group withdraw after FMT infusion. Finally, 29 patients allocated to FMT plus metformin (n=8), FMT alone (n=9), or metformin (n=12) completed their follow-up assessment at both baseline and week 4 (Consort diagram of the study flow. FMT, faecal microbiota transplantation. | PMC9872724 | |
Blood glucose, insulin resistance, and BMI improvement after intervention | fasting blood glucose, cholesterol;TP, T2DM | INSULIN RESISTANCE, PCP | Participants in the three treatment groups had significant (P<0.05) improvement in fasting blood glucose (FBG); postprandial blood glucose (PBG), hemoglobin A1c (HbA1c), and HOMA-HBCI at week 4 after intervention compared with the baseline (Clinical data included in this study.The data are shown as the mean±SD. N=12 in the metformin group, N=9 in the FMT group and n=8 in the FMT plus metformin group for all outcomes. FMT, fecal microbiota transplantation; FBG, fasting blood glucose; PBG, postprandial blood glucose; HbA1c, hemoglobin A1c.HOMA-HBCI=20×FINS/(FBG-3.5); BMI, body mass index; HOMA-IR=(FBG×FINS)/22.5; PCP, postprandial c-peptide; FINS, fasting insulin; AFU, α-L-fucosidase; FCP, fasting c-peptide; GGT, γ-glutamyl transpeptadase; D-BIL, direct bilirubin; ALP, alkaline phosphatase; TBA, total bile acid; TBIL, total bilirubin; APO-B, apolipoprotein B; PINS, postprandial insulin; LDL, low-density lipoprotein; BUN, urea nitrogen; ALT, alanine aminotransferase; HDLC, high-density lipoprotein; CHE, cholinesterase;UA, uric acid; TG, triglyceride; TC, total cholesterol;TP, total protein; MAO, monoamine oxidase; I-BIL, indirect bilirubin; AST, aspartate aminotransferase; APOA, apolipoprotein A.Bold values represents statistically significant indicators.General mechanism of FMT improving insulin resistance.We further evaluated the magnitude of change among the three groups. Percentages of improvements in PBG, FBG, HOMA-IR, BMI, AST/ALT and ALP were significantly higher in the FMT alone and FMT plus metformin than in metformin group (Fold changes of clinical indexes based on week 4 divided by week 0 in T2DM patients with different interventions. Pairwise comparisons between groups were conducted using the Wilcox test. Metformin, n=12 patients; FMT, n=9 patients; FMT plus metformin, n=8 patients. | PMC9872724 |
Microbiota alterations associated with FMT intervention | T2DM | Microbial richness (observed taxa and Chao1) and Shannon diversity were obviously (P < 0.05) improved at week 4 after FMT compared with the baseline, although the significance is marginal. Moreover, the evenness was significantly (P<0.05) increased by FMT in FMT alone group at week 4 (Changes in gut microbiota between week 0 and week 4 in T2DM patients after interventions. | PMC9872724 | |
β-diversity and microbial colonization | The results of β-diversity based on Euclidean distance showed that the intestinal microbiota changed at week 4 compared with week 0 with the three treatments. The gut microbial communities in FMT plus metformin group were significantly different (PERMANOVA, p < 0.05) between week 4 and week 0, while there was no significant difference in FMT alone nor in metformin group (Donor-recipient gut microbiota correlation rate. Subjects with effective engraftment: Percentage of subjects with ≥20% donor-associated microbiota.The colonization of donor-derived microbial species was analyzed and detected in post-FMT samples from all recipients in both FMT alone and FMT plus metformin groups, with percentage ranging from 3.1% to 73.7%.The results showed that 6 patients (66.7%) in the FMT group and 5 patients (62.5%) in the FMT plus metformin group achieved ≥20% donor-derived microbial species, which was considered as effective colonization. However, there was no significant difference in colonization rate between the two groups (p > 0.05) ( | PMC9872724 | ||
Taxa significantly associated with clinical improvements | T2D, T2DM | To explore the taxa associated with improvement in clinical efficacy, the differences between baseline and week 4 after intervention in FMT alone and FMT plus metformin groups were analyzed by Wilcoxon-rank sum test. A total of 7 phyla, 57 families, and 133 genera level were significantly (p < 0.05) different after intervention in FMT alone group, while the numbers were 10, 63 and 206 in the FMT plus metformin group (The commonly and significantly different species of between the FMT alone and FMT plus metformin groups.Microbial species significantly changed after intervention and their correlation with clinical indicators. Since improvement in HOMA-IR is urgent in treatment of T2D, we further explored the species by conducting correlation analysis between HOMAR-IR and the species significantly different either after FMT or FMT plus metformin, based on samples from T2DM patients at baseline and week 4 after intervention. The results showed that most of the significantly associated species were positively correlated with HOMA-IR ( | PMC9872724 | |
Discussion | diarrhea, cramps, constipation, hypoglycemia, abdominal distension, T2DM | HYPOGLYCEMIA, INSULIN RESISTANCE, DISEASES, SIDE EFFECTS | This study aimed to evaluate the improvements of T2DM patients and their gut microbiota by FMT alone and FMT plus metformin, compared with metformin. Results showed that FMT alone and FMT plus metformin significantly improved insulin resistance (HOMA-IR), HOMA-HBCI, BMI, FBG, and PBG within 4 weeks after intervention, and modified gut microbial communities by colonization of donor-derived microbiota. Correlation analysis revealed that Metformin is currently widely used as the first-line drug for the treatment of T2DM patients, as recommended by clinical guidelines, due to the improved glycemic profile and reduction in cardiovascular mortality without the risk of hypoglycemia and/or body weight gains (The patients included in our cohort were diagnosed with T2DM and were not receiving prior regular drug treatment or dietary intervention. These T2DM patients had poorly controlled blood glucose or serious insulin resistance and received no other medications for the treatment of other diseases. During the observation period, the enrolled patients did not perform any physical exercise other than daily life activities and received generally consistent dietary regulation. This design enabled us to diminish the effects of major confounding factors that have a known impact on the gut microbiome. Clinically, not all T2DM patients benefit from the use of metformin or respond to metformin quickly. For example, some patients exhibit strong insulin resistance and weak insulin secretion function despite metformin treatment. Therefore, FMT was used to assist metformin treatment in these patients to quickly improve their sensitivity to metformin.The present study demonstrated that, although metformin could improve the blood glucose, the addition of FMT promoted the improvement further. Many studies have shown that gut microbiota are closely related to glucose metabolism (A decent engraftment of donor-associated microbiota taxa in recipients during the FMT procedure is one of the prerequisites that guarantees the efficacy of FMT. It is generally believed that the diversity of gut microbiota is closely related to gut health, and the colonization rate of donor flora in the recipient is an important indicator to evaluate the success rate of transplantation. In our study, about 2/3 of the FMT group and the FMT plus metformin group reached the target of ≥ 20% donor derived microbial species, which was significantly increased by 23 compared with other previous studies (Side effects of FMT include mild and self-limiting abdominal discomfort, cramps, abdominal distension, diarrhea or constipation, and very few diseases that cannot pass screening tests (Our study has several limitations. First, the relatively small sample size was not sufficient to evaluate the subtle differences or mechanisms associated with metformin treatment with or without FMT therapies. Second, the study period was limited to 4 weeks, restricting our understanding of the relationship between long-term clinical efficacy and engraftment of donor-associated microbiota. Third, due to scarcity of the donors, we used multi-donor FMT at different FMT times to enhance the microbial diversity transferred to recipients. However, a fixed donor choice based on donor-recipients matching for patients would help eliminate any confounding factors. | PMC9872724 |
Conclusion | T2DM | In conclusion, In conclusion, our study showed that FMT improved the BMI, PBG, HbA1c, FBG, HOMA-HBCI, and HOMA-IR of T2DM patients in 4 weeks and also promoted the engraftment of donor-associated microbiota in participants. Results from our trial will serve as a basis for the long-term intervention of FMT in T2DM patients and the further development of novel biotherapeutic strategies aimed at combatting T2DM through the safe, effective, and affordable bacterial formulations. | PMC9872724 | |
Data availability statement | The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ | PMC9872724 | ||
Ethics statement | The studies involving human participants were reviewed and approved by Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College Ethics Committee in Shantou, China(Ethics number:LHLL2019001), and was registered at Chinses Clinical Trial Registry. (Registration number: ChiCTR1900024636).( | PMC9872724 | ||
Author contributions | ZW | ZW and BZ, conceptualization, investigation, methodology, and writing-original draft. RX and FC, conceptualization, investigation, methodology, writing-review and editing. DZ and BC, conceptualization, investigation, writing-review and editing. AL and CZ, conceptualization, supervision, writing-review and editing. DH, XL, and SZ, conceptualization, investigation, writing-review and editing. KH and YC, conceptualization, formal analysis, investigation, visualization, supervision, writing-review and editing, project administration, and funding acquisition. All authors contributed to the article and approved the submitted version. | PMC9872724 | |
Conflict of interest | The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. | PMC9872724 | ||
Publisher’s note | All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | PMC9872724 | ||
Supplementary material | The Supplementary Material for this article can be found online at: Basic information and clinical data of participants.Click here for additional data file. | PMC9872724 | ||
References | PMC9872724 | |||
Purpose | mTNBC | TRIPLE-NEGATIVE BREAST CANCER | In a phase II trial in patients with metastatic triple-negative breast cancer (mTNBC; NCT02978716), administering trilaciclib prior to gemcitabine plus carboplatin (GCb) enhanced T-cell activation and improved overall survival versus GCb alone. The survival benefit was more pronounced in patients with higher immune-related gene expression. We assessed immune cell subsets and used molecular profiling to further elucidate effects on antitumor immunity. | PMC10361859 |
Methods | TNBC, mTNBC, Tumor, tumor | TUMOR, INFLAMMATION, TUMOR | Patients with mTNBC and ≤ 2 prior chemotherapy regimens for locally recurrent TNBC or mTNBC were randomized 1:1:1 to GCb on days 1 and 8, trilaciclib prior to GCb on days 1 and 8, or trilaciclib alone on days 1 and 8, and prior to GCb on days 2 and 9. Gene expression, immune cell populations, and Tumor Inflammation Signature (TIS) scores were assessed in baseline tumor samples, with flow cytometric analysis and intracellular and surface cytokine staining used to assess immune cell populations and function. | PMC10361859 |
Results | After two cycles, the trilaciclib plus GCb group ( | PMC10361859 | ||
Conclusion | TNBC | The results suggest that administering trilaciclib prior to GCb may modulate the composition and response of immune cell subsets to TNBC.
| PMC10361859 | |
Keywords | PMC10361859 | |||
Introduction | tumor, breast cancer, TNBC, mTNBC, chemotherapy-induced damage | TRIPLE-NEGATIVE BREAST CANCER, TUMOR, INVASIVE BREAST CANCER, BREAST CANCER | Triple-negative breast cancer (TNBC) is a specific subtype of breast cancer that is associated with high invasiveness, high metastatic potential, proneness to relapse, and poor prognosis. Patients with TNBC have fewer treatment options available to them than those with other types of invasive breast cancer [Trilaciclib is an intravenous myeloprotection therapy that is administered as a 30-min infusion within 4 h prior to the start of chemotherapy on each day chemotherapy is administered. Trilaciclib transiently arrests cyclin-dependent kinase 4/6 (CDK4/6)-dependent hematopoietic stem and progenitor and immune cells in the G1 phase of the cell cycle during chemotherapy exposure, protecting these cells from chemotherapy-induced damage [Trilaciclib has been shown to favorably alter the tumor immune microenvironment in in vivo murine syngeneic models [The efficacy and safety of trilaciclib in patients with mTNBC have been investigated in a randomized phase II trial (NCT02978716) [The aim of the current analysis was to further investigate potential immune mechanisms of trilaciclib in mTNBC through the analysis of immune cell subsets and molecular profiling in peripheral blood and tumor samples, respectively. | PMC10361859 |
Materials and methods | PMC10361859 | |||
Study design and participants | TNBC, mTNBC, NCT02978716 | This analysis is based on data from a multicenter, randomized, open-label, phase II trial including patients aged ≥ 18 years with mTNBC who had received up to two prior chemotherapy regimens for locally recurrent TNBC or mTNBC (NCT02978716) [ | PMC10361859 | |
Antitumor efficacy endpoints and assessments | tumor, tumors, TNBC tumors | DISEASE PROGRESSION, TUMOR, MAY, SECONDARY, TUMORS | Efficacy and survival outcomes were analyzed as prespecified secondary endpoints and included objective response rate (confirmed complete or partial response) assessed in response-evaluable patients, and progression-free survival and OS, assessed in the intention-to-treat population. Objective response rate and progression-free survival were investigator assessed according to Response Evaluation Criteria in Solid Tumours (RECIST) version 1.1, based on the May 15, 2020, data cut-off. For tumor assessment, computed tomography or magnetic resonance imaging was performed at screening and at protocol-specified intervals (every 9 weeks for the first 6 months, then every 12 weeks thereafter) until disease progression, withdrawal of consent, or receipt of subsequent anticancer therapy. OS was analyzed following the final database lock on July 17, 2020. Genetic and/or expression markers in blood and tumors and immunologic markers, including PD-L1 expression, were analyzed as post hoc exploratory objectives. Baseline PD-L1 status was measured using the Ventana SP142 PD-L1 assay; tumors were scored as PD-L1 positive if the proportion of PD-L1-expressing tumor-infiltrating immune cells was ≥ 1% and PD-L1 negative if < 1%, per the assay interpretation guide for TNBC tumors [ | PMC10361859 |
Peripheral immune cell population and function analysis | BLOOD | Peripheral blood was collected prior to and during treatment for flow cytometric analysis; for the purposes of this analysis, samples were collected prior to treatment on the first day of the first and third treatment cycles (C1D1 and C3D1, respectively). Blood was collected in Cyto-Chex | PMC10361859 | |
Tumor gene expression analysis | tumor | TUMOR | Genomic DNA and total RNA were simultaneously purified and sequenced as previously described from formalin-fixed, paraffin-embedded (FFPE) diagnostic tumor samples collected at baseline [ | PMC10361859 |
Tumor immune microenvironment analysis | Tumor | INFLAMMATION, TUMOR | The Tumor Inflammation Signature (TIS) [ | PMC10361859 |
Statistical methods | Statistical comparisons of cell numbers/ratios and TIS scores for different time points and patient groups were performed using the Wilcoxon signed-rank test. Plots were created using the ggplot2 and EnhancedVolcano R packages [ | PMC10361859 | ||
Results | PMC10361859 | |||
Participants and treatment | As of July 17, 2020, median (range) duration of follow-up was 8.4 (0.1–25.7) months for the 34 patients who received GCb alone, 14.0 (1.3–33.6) months for the 33 patients who received trilaciclib prior to GCb on days 1 and 8, and 15.3 (3.5–33.7) months for the 35 patients who received trilaciclib alone on days 1 and 8 and trilaciclib prior to GCb on days 2 and 9. Antitumor response status was available for 58 of the 68 patients who received trilaciclib prior to GCb: 27 patients (46.6%) had an antitumor response with trilaciclib plus GCb (trilaciclib responders), and 31 (53.4%) had no response (non‑responders). | PMC10361859 | ||
Analysis of immune subsets and T-cell function at C1D1 versus C3D1 in patients receiving trilaciclib prior to GCb or GCb alone | Patients who received trilaciclib prior to GCb had fewer total T cells (Changes to | PMC10361859 | ||
Immune cell populations and T-cell function analysis among trilaciclib responders versus non-responders | To determine if the impact on T-cell effector function was attributable to clinical outcomes, data from responders and non‑responders who were treated with trilaciclib were compared. After two cycles, T-cell numbers were maintained in trilaciclib responders but significantly reduced in non‑responders (Changes to immune cell populations in peripheral blood over two cycles (C1D1 vs. C3D1) for trilaciclib responders and non-responders. Changes to | PMC10361859 | ||
Discussion | tumor, neutropenia, T-cell infiltration, mTNBC, chemotherapy-induced damage | TUMOR, NEUTROPENIA, BREAST CANCER, SECONDARY, ARREST | Data from this exploratory analysis provide further evidence of a trilaciclib-mediated antitumor immune response among patients with mTNBC [These findings support prior research indicating that, following transient G1 arrest, the proportion of immunosuppressive cells in the tumor microenvironment is decreased and effector T-cell function is enhanced [Data from diagnostic tumor samples collected at baseline showed that genes involved in immune cell activation were upregulated among trilaciclib responders, and there was a trend toward higher TIS scores. In general, although higher TIS scores are not associated with increased OS in breast cancer, they are associated with improved prognosis in those patients with the highest 10% of TIS scores [A trend for higher T-cell exhaustion at baseline may indicate that patients had a greater existing immune response and, consequently, higher existing T-cell infiltration into the tumor. Exhausted T-cell profiles in the tumor microenvironment [Additional analyses were conducted to compare results by PD-L1 status at baseline. Increased levels of peripheral memory CD8+ T cells and naïve CD8+ T cells were observed after two cycles in trilaciclib responders, regardless of PD-L1 status. However, greater peripheral immune responses and a trend toward an enriched TIS were identified in PD-L1-positive trilaciclib responders at baseline compared with non‑responders. These data support previous research showing that CDK4/6 inhibition promotes the formation of memory CD8+ T cells, which is proposed to occur via upregulation of MXD4 and resultant downregulation of Myc activity during T-cell activation [Limitations of this study include the small sample size, particularly in the responder subsets. Moreover, antitumor efficacy outcomes were not the primary study endpoints. The sample size was powered to show superiority among patients who received trilaciclib prior to GCb over those who received GCb alone for at least one primary endpoint (duration of severe neutropenia in cycle 1 or occurrence of severe neutropenia during the treatment period). As such, comparisons of secondary endpoints, including antitumor responses, should be considered exploratory and interpreted with caution. However, the findings of this hypothesis-generating analysis were consistent with, and supportive of, a previous exploratory analysis of the same study [Overall, these data contribute to a growing body of evidence that transient administration of trilaciclib prior to GCb may enhance antitumor efficacy by both protecting immune cells from chemotherapy-induced damage and modulating the composition and response of immune cell subsets. Data from ongoing clinical studies are critical to confirming the underlying immune mechanisms and to identifying biomarkers that will clearly distinguish between trilaciclib responders and non‑responders. | PMC10361859 |
Acknowledgements | We acknowledge Aaron Stevens and Jessica Sorrentino, former employees of G1 Therapeutics, Inc., for their contributions toward this analysis and interpretation of data. We also thank all the patients, their families, and study personnel for participating in the study. | PMC10361859 | ||
Author contributions | ART and JOS contributed to the design and implementation of the clinical research and to the acquisition of data. SC, SA, and JSY conceived and designed the analysis. All authors were responsible for the analysis and interpretation of results; provided critical feedback and helped shape the research, analysis, and development of the manuscript; and read and approved the final manuscript. | PMC10361859 | ||
Funding | This work was supported by G1 Therapeutics, Inc. The study sponsor was involved in the study design, in the collection, analysis, and interpretation of the data, in the writing of the report, and in the decision to submit the paper for publication. Medical writing assistance was provided by Alligent Europe (Envision Pharma Group), funded by G1 Therapeutics, Inc. | PMC10361859 | ||
Data availability | All data generated or analyzed during this study are included in this published article. | PMC10361859 | ||
Declarations | PMC10361859 | |||
Conflict of interest | Sarah Ahn | ONCOLOGY | Antoinette R. Tan reports institutional clinical trial support and personal fees from G1 Therapeutics, Inc.; outside of the submitted work, institutional clinical trial support from Arvinas, Genentech/Roche, Merck, and Pfizer, and personal fees from AstraZeneca, Genentech/Roche, Jazz Pharmaceuticals, Novartis, Puma, Seagen, and Stemline Therapeutics. Joyce O’Shaughnessy reports institutional clinical trial support and personal fees from G1 Therapeutics, Inc.; outside of the submitted work, personal fees from AbbVie, Agendia, Amgen, Aptitude Health, AstraZeneca, BMS, Celgene, Eisai, Genentech, Immunomedics, Ipsen, Jounce Therapeutics, Lilly, Merck, Myriad, Novartis, Odonate Therapeutics, Pfizer, Prime Oncology, Puma Biotechnology, Roche, Seattle Genetics, and Syndax Pharmaceuticals. Subing Cao and Sarah Ahn (at the time of the study), and John S. Yi are paid employees and shareowners of G1 Therapeutics, Inc. | PMC10361859 |
Ethical approval | The study (NCT02978716) was designed and conducted in accordance with the Declaration of Helsinki and the Good Clinical Practice guidelines of the International Council for Harmonisation. The protocol and all study-related materials were approved by the institutional review board or independent ethics committee of each investigational site. | PMC10361859 | ||
Consent to participate | Written informed consent was obtained from all individual participants included in the study. | PMC10361859 | ||
Consent to publish | Not applicable. | PMC10361859 | ||
References | PMC10361859 | |||
Subject terms | Our randomized controlled simulation study aimed to compare the CPR quality, time-related factors, attitude and self-assessment of non-healthcare university students (aged 18–25) compared video-assisted (V-CPR, n = 50) with telephone-assisted (T-CPR, n = 49) and unassisted (U-CPR, n = 48) CPR in a simulation setting. Regarding to chest compression depth, no difference was found between the three groups (p = 0.065): 41.8 mm, SD = 9.9 in the V-CPR; 35.9 mm, SD = 11.6 in the T-CPR; and 39.4 mm, SD = 15.6 in the U-CPR group. The mean chest compression rate was the best in the V-CPR group (100.9 minOpen access funding provided by University of Pécs. | PMC10495456 | ||
Introduction | death, Sudden cardiac arrest, OHCA, cardiac arrest, T-CPRThe, chest compression | CARDIAC ARREST | Sudden cardiac arrest is a major public health problem worldwide and it is one of the leading causes of death in industrialized countriesIn the majority of the cases, the bystanders who call the ambulance are laypeople, for whom the identification of OHCA is difficult without experience. Therefore, EMS dispatchers play an important role to recognize cardiac arrest and give help to the lay first responder via telephone CPR (T-CPR) which improves survival ratesThe current technology allows the live video connection between the scene and the dispatcher which provides the opportunity for video-assisted CPR (V-CPR). In some prior studies, V-CPR showed higher efficacy in some aspects of chest compressions than T-CPRThe aim of this study was to compare the CPR quality (chest compression depth and rate, hand position), the CPR-related time intervals (time of check the breathing, time to call the ambulance, time to the first chest compression), and the attitude and self-assessment of lay responders comparing unassisted CPR (U-CPR), T-CPR and V-CPR. We hypothesized that the quality and effectiveness of the V-CPR method are superior to the quality of U-CPR and T-CPR in a simulation setting. | PMC10495456 |
Methods | PMC10495456 | |||
Study design | A randomized controlled, superiority, simulation trial was performed. The Consolidated Standards of Reporting Trials (CONSORT) reporting guideline was followedOur study was registered at ClinicalTrials.gov (registration number: NCT05639868; date of first registration: 06/12/2022). | PMC10495456 | ||
Participants | University students from non-healthcare areas were recruited in our study from the Eötvös Lóránd University, Savaria University Centre, Szombathely, Hungary. The study was conducted between December 2022 and January 2023. Eligible for inclusion were university students. A written form was sent via email and students were asked to contact the trial manager if they were willing to participate. Participants who were not capable to perform CPR (e.g. physical or mental impairment) were excluded from the study. Participants did not receive any compensation for their participation. | PMC10495456 | ||
Randomization and blinding | Participants were randomly assigned into three different groups before the assessment: U-CPR; T-CPR; and V-CPR. During randomization, the permuted block technique was used with a 1:1:1 ratio. After randomization, study participants were informed about their allocated group, but were blinded to the purpose of the study. The dispatchers, assessors and the operator were informed about their tasks in the different groups but were blinded to the study design and the outcomes. | PMC10495456 | ||
Intervention | SE | Participants were accompanied into a room by a study operator who was equipped with a smartphone (iPhone 2013, Apple Inc., USA). Based on a prior study, video quality had no significant impact on the evaluation of CPR performanceDuring the scenario, the participants should perform the initial examinations (check the safety of the environment, check the response and the breathing of the victim), give instructions to the study operator to call the ambulance and start chest compressions. Related to the duration of the intervention, the clock started when the participant entered the room. After that, every participant should perform chest compression-only CPR for 2 min (because based on the current guidelines changing the rescuer during CPR is recommended every 2 min)Another room was set up for the dispatcher with a smartphone (for audio communication; iPhone SE 2020, Apple Inc., USA) and a tablet (for video communication; iPad Air 8th Gen, Apple Inc., USA). Two dispatchers were involved in the study who were familiar and experienced with the Hungarian emergency dispatch system and were informed about the study methods. In the U-CPR group, the dispatcher gave the information to the caller that they should perform chest compressions until the ambulance arrives. After that, the call ended and no further instructions were received from the dispatcher. In the T-CPR and V-CPR groups, the dispatcher gave instructions related to high-quality chest compressions based on the current ERC guidelinesDuring the scenario, the smartphone and the tablet were linked to the internet via secure WiFi (bandwidth 1000 mbits | PMC10495456 | |
Data collection | cardiac arrest | CARDIAC ARREST | The quality of chest compressions (depth and rate) were measured by the AMBU CPR software and were analyzed retrospectively based on the recorded reports. For calculating proportions of correct chest compression parameters, software recorded data were dichotomized to „correct” (within the intervals described in the guidelines) and „incorrect” (outside the intervals described in the guidelines) categories. Scenarios were also video recorded and analyzed by assessors who were emergency professionals (two paramedics) familiar with Basic Life Support (BLS) education who are familiar with CPR quality assessment. For recording, a camera (Nikon D750, Nikon Corporation, Tokyo, Japan) with a resolution of 1920 × 1080 pictures was pre-installed on a tripod in the room. The camera picture covered the room entrance, the manikin and the activity of the participants. At this latter point, correct hand position during CPR, time of check the breathing, time to call the ambulance and time to the first chest compression were measured. For time-related data, the clock was started when the participants entered the room and stopped after 2 min of chest compressions.Sociodemographic data (age, body weight and height, prior first aid training, prior real-life CPR experience) were collected by a study assistant immediately after the scenario. Collected data were anonymized. In addition, self-assessment in all groups, and experiences and attitudes related to dispatcher-assisted CPR in T-CPR and V-CPR groups were also measured by filling out an online survey after the scenario (5 items for U-CPR; 6 items for T-CPR and V-CPR). For filling out the survey, a tablet (iPad Air 8th Gen, Apple Inc., USA) was used with the assistance of a study operator. A 4-point Likert-scale was used in the following questions: (1) “How did you feel during the scenario?”; (2) “How calm were you during the scenario?”; (3) “Did you perform CPR in the right way?”; (4) “Were the dispatcher’s instructions useful for you during the scenario?”; (5) “Would it be useful to get instructions from the dispatcher during the scenario?”; (6) “How motivating was it to communicate with the dispatcher during the scenario?”. A “Yes/No” answer could be given to the following question: “Would you use the V-CPR method in a real cardiac arrest situation?”. | PMC10495456 |
Outcomes | SECONDARY | The primary outcome of the study was the quality of chest compressions, measured by the mean depth. The evaluation of data was based on the current ERC guidelines (depth of 50–60 mm)The secondary outcome of the study was chest compression quality expressed by rate (minFurthermore, the participant-centered secondary outcome was the evaluation of self-assessment and attitude toward dispatcher-assisted CPR. Data collection and analysis were based on the online survey filled out by the participants immediately after the scenario. | PMC10495456 | |
Sample size calculation | Sample size was calculated to detect a 5 mm difference in chest compression depth between the groups based on prior studies | PMC10495456 | ||
Statistics | To describe the sample, descriptive statistics were used. Study parameters were assessed for normal distribution and reported as numbers (percentages) and means (SDs). Study parameters were assessed for normality by using Shapiro–Wilk test which indicated normal distribution. Continuous variables were compared using ANOVA and Bonferroni post hoc test as appropriate. Categorical variables were compared using Chi-square test or Fisher’s-exact test as appropriate. A two-tailed p-value of < 0.05 was considered to be statistically significant. Statistical analysis was conducted using SPSS 24.0 (Statistics Package for Social Sciences, Chicago, IL, USA). | PMC10495456 | ||
Results | PMC10495456 | |||
Participants flow, recruitment, and baseline characteristics | SD | In total, 207 emails were sent to the university students (this was the total number of the students on the campus). One hundred and fifty of them responded that they would like to participate our study, so 150 participants were assessed for eligibility. None of the participants were excluded before the randomization. Therefore, 150 participants were randomized: 50 to the V-CPR group, 50 to the T-CPR group, and 50 to the U-CPR group. Three of the participants were excluded (two from the U-CPR group and one from the T-CPR group) because of a technical issue during data collection [the CPR software did not record data]). After exclusions, the total number of participants was 147, respectively. The study flowchart is visible in Fig. CONSORT diagram. U-CPR, unassisted cardiopulmonary resuscitation; T-CPR, telephone-assisted cardiopulmonary resuscitation; V-CPR, video-assisted cardiopulmonary resuscitation.Most of the participants were female (103, 70.1%). The mean age was 20.3 years (SD = 1.4), and the mean BMI was 23.1 kg/mBasic characteristics of the participants.U-CPR, unassisted cardiopulmonary resuscitation; T-CPR, telephone-assisted cardiopulmonary resuscitation; V-CPR, video-assisted cardiopulmonary resuscitation; SD, standard deviation; BMI, body mass index. | PMC10495456 | |
Discussion | OHCA, cardiac arrest | CARDIAC ARREST | In this randomized controlled simulation study, we measured chest compression effectiveness (rate, depth and hand position) and time-related factors (time of check the breathing, time to call the ambulance, and time to the first chest compression) in a cardiac arrest scenario comparing V-CPR, T-CPR and U-CPR groups. In addition, we collected data about CPR self-assessment and attitudes toward V-CPR technology. Since the effectiveness of V-CPR is affected by several factors, we tried to give a wide picture of the topic (CPR effectiveness, time-related factors, attitude and self-assessment). Our results showed that V-CPR method performed by lay responders could lead to higher-quality chest compressions compared to T-CPR and U-CPR. However, V-CPR instructions were not enough to achieve high-quality chest compression depth related to the ERC guidelines in the majority of the casesEarly recognition of OHCA, activation of the EMS, and performing high-quality CPR can improve survival rate which can be supported by dispatcher-assisted CPRIn our study, participants performed chest compression-only CPR because it is the recommended protocol during dispatcher-assisted resuscitation in HungaryAnalyzing data from another perspective, we measured time-related parameters. The time of check the breathing was the longest in the V-CPR group. The reason for this result could be that the dispatcher fixed some problems in many cases and gave real-time feedback based on the video picture (e.g. participants did not tilt the head back during the procedure of check the breathing). Participants in the V-CPR group called the ambulance earlier than in the T-CPR and U-CPR groups. It can be explained with the prior information that they will be able to communicate with the dispatcher via a video call if they need some support. Time to the first chest compression was shorter in the V-CPR group than in the T-CPR group, however, was longer than in the U-CPR group. The difference between V-CPR and T-CPR can be explained with the more clear instructions by the dispatchers: in the V-CPR group, dispatchers could see the situation and were able to give adequate prompts, and it was not necessary to ask the lay rescuer for any feedback which could decrease the delays during the process. In addition, the difference between the V-CPR and U-CPR groups can be explained by the fact, that the process is faster (though not necessarily more efficient) when lay rescuers can do the process without any external instructions. Based on a systematic review, dispatcher-assisted CPR demonstrated inferior outcomes compared to unassisted (bystander-initiated) CPRIn dispatcher-assisted CPR, human factors are essential, as well (e.g. trained dispatchers, physical abilities and attitudes of the lay responders)Based on our results, V-CPR is feasible to improve the quality of CPR compared to T-CPR and U-CPR. However, analyzing the data from the view of real-life requirements (e.g. international guidelines), only a minority of the V-CPR participants were able to achieve high-quality chest compressions in all aspects together which conformed to the ERC guidelinesOur study has several limitations. First, since V-CPR is not been implemented in real emergency situations in Hungary yet, we could not set up a „real dispatcher room” fitting the requirements of V-CPR, and we did not have a standardized V-CPR protocol (dispatchers used the usual T-CPR protocol with some modifications expanded by the live video picture). Second, our study was made under optimal circumstances (sufficient light, stable WiFi connection, no negative environmental and weather factors, etc.), and we used a CPR manikin as the victim during a 2 min long scenario. In addition, participants were informed about the opportunities of the different groups which limited the realism. Regarding these facts, we do not know, how our participants would react in a possible real-life OHCA situation, or what would be the results during a longer scenario. Third, we used a study operator who handled the smartphone and managed the emergency call. In a real emergency situation, a second person may not always be present and/or is not prepared with the usage of the V-CPR technology. Furthermore, the participants in our study were university students (young adults). Examining different age groups of lay responders would lead to other results. | PMC10495456 |
Conclusion | We could not show any difference in chest compression depth comparing V-CPR with T-CPR and U-CPR groups in a simulation setting. However, V-CPR was superior to T-CPR and U-CPR in chest compression rate and correct hand position. | PMC10495456 | ||
Supplementary Information | The online version contains supplementary material available at 10.1038/s41598-023-42131-z. | PMC10495456 | ||
Acknowledgements | The authors would like to thank all the students who participated in the study. | PMC10495456 | ||
Author contributions | V.S., H.B. and B.B. participated in designing the study. H.B. obtained funding for the study. V.S. and H.B. were responsible for the data collection. V.S., D.N., H.B. and B.H. interpreted the data and performed statistical analyses. V.S., J.B., B.B. and H.B. participated in writing the manuscript. All authors reviewed and approved the final version of the manuscript. | PMC10495456 | ||
Funding | Open access funding provided by University of Pécs. This study was supported by the ÚNKP-22-4-I New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund. The funding agency had no role in the design of the study and collection, analysis, and interpretation of data, and in writing the manuscript. | PMC10495456 | ||
Data availability | The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. | PMC10495456 | ||
Competing interests | The authors declare no competing interests. | PMC10495456 | ||
References | PMC10495456 | |||
Background | High prevalence of excessive screen time among preschool children is attributable to certain parental factors such as lack of knowledge, false perception about screen time, and inadequate skills. Lack of strategies to implement screen time guidelines, in addition to multiple commitments that may hinder parents from face-to-face interventions, demands the need to develop a technology-based parent-friendly screen time reduction intervention. | PMC10196888 | ||
Objective | This study aims to develop, implement, and evaluate the effectiveness of | PMC10196888 | ||
Methods | SECONDARY | A single-blind, 2-arm cluster randomized controlled trial was conducted among 360 mother-child dyads attending government preschools in the Petaling district, who were randomly allocated into the intervention and waitlist control groups between March 2021 and December 2021. This 4-week intervention, developed using whiteboard animation videos, infographics, and a problem-solving session, was delivered via WhatsApp (WhatsApp Inc). Primary outcome was the child’s screen time, whereas secondary outcomes included mother’s screen time knowledge, perception about the influence of screen time on the child’s well-being, self-efficacy to reduce the child’s screen time and increase physical activity, mother’s screen time, and presence of screen device in the child’s bedroom. Validated self-administered questionnaires were administered at baseline, immediately after the intervention, and 3 months after the intervention. The intervention’s effectiveness was evaluated using generalized linear mixed models. | PMC10196888 | |
Results | A total of 352 dyads completed the study, giving an attrition rate of 2.2% (8/360). At 3 months after the intervention, the intervention group showed significantly reduced child’s screen time compared with the control group (β=−202.29, 95% CI −224.48 to −180.10; | PMC10196888 | ||
Conclusions | The | PMC10196888 | ||
Trial Registration | Thai Clinical Trial Registry (TCTR) TCTR20201010002; https://tinyurl.com/5frpma4b | PMC10196888 | ||
Introduction | PMC10196888 | |||
Background | Screen time is defined as the time occupied by screen-based activities on visual devices such as television, smartphones, computers, video games, tablets and iPads, and other handheld gadgets [Despite some reported advantages of screen time when digital devices are used in moderation under parental guidance, excessive use beyond the recommended limits has been associated with multiple health risks, especially among young children. A positive association was detected between screen time with the child’s BMI | PMC10196888 | ||
Previous Studies | During the early childhood period of preschool years, parents play the most fundamental role in shaping a child’s habits [ | PMC10196888 | ||
Objectives | This study aimed to develop, implement, and evaluate the effectiveness of a parental digital health education intervention named | PMC10196888 | ||
Methods | PMC10196888 | |||
Study Design | RECRUITMENT | This study used a 2-arm, parallel, cluster randomized controlled trial (RCT) design based on the CONSORT (Consolidated Standards of Reporting Trials) guideline’s extension for clustered RCTs. The clusters in this RCT were government preschools under the Community Development Department that provided education to children aged 3 to 4 years from low-income communities. All clusters were randomly assigned into the intervention group receiving the CONSORT (Consolidated Standards of Reporting Trials) diagram describing the recruitment and progress of participants throughout the study period. T0: baseline; T1: immediately after the intervention; T2: 3 months after the intervention. | PMC10196888 | |
Study Setting and Recruitment | physical disabilities | RECRUITMENT, RECRUITMENT | Selangor is the most populated state in Malaysia, with the highest number of children (1.8 million children) [A total of 16 government preschools in the Petaling district were randomly selected. The operators of the preschools were then approached to participate in the study via phone calls and meetings. Recruitment of participants was originally planned for January 2020. However, owing to the closure of schools following COVID-19–related lockdowns, it was postponed until March 2021 to June 2021. The inclusion criteria for preschools were government preschools with classes for children aged 3 to 4 years. Regarding the mother-child dyad, those who were included were mothers with preschoolers aged 3 to 4 years, registered with government preschools in Petaling during the recruitment period in 2021 who reported their children’s screen time as >1 hour per day in the past month. They also needed to have access to smartphones and be willing to use WhatsApp as a medium of interaction. Mothers with physical or mental disabilities and children with physical disabilities, as certified by medical practitioners, were excluded from the study.To recruit the participants, mothers of children aged 3 to 4 years within the designated clusters were identified from the enrollment database for the year 2021 and recruited. Preschool educators distributed electronic pamphlets containing brief information about the study to all mothers. Interested mothers can self-register using a Google Form link in the pamphlet. Eligible mothers who consented to participate were then added to a WhatsApp group managed by a research assistant. All participants were informed that they would receive the relevant interventions in stages within the next 6 months. Hence, they were blinded and unaware of their group allocation throughout the study. | PMC10196888 |
Sample Size Calculation | The sample size was calculated based on the primary outcome of detecting the mean screen time differences between the intervention group and control group. To detect a reduction of 43.2 (SD 105) minutes of screen time per day [ | PMC10196888 | ||
Randomization and Blinding | Random sequence generation was conducted by a research assistant at the cluster level to avoid contamination. All eligible preschools were randomly allocated into the | PMC10196888 | ||
Intervention | As screen time was widely known to displace the time spent on physical activities, the term Following the COVID-19 pandemic, many health care professionals have strived to identify alternative evidence-based measures to deliver effective health education interventions at a time when face-to-face interactions were impossible. WhatsApp is an effective mode for delivering health education interventions [The intervention module was developed through a process of consultation with a panel of health experts. To ensure its local cultural suitability, it was first pretested among 35 mother-child dyads of preschool children, who were not part of the main study. The delivery of the module was performed by the primary researcher, a physician. The intervention module took 4 weeks to be completed. Overall, 3 videos relevant to the educational content were created using whiteboard animation, and an additional video that portrayed success stories from other mothers was also included. A screenshot of the intervention is available in | PMC10196888 | ||
Outcome | PMC10196888 | |||
Primary Outcome Measure | The primary outcome of this study was the average screen time per day of the child, obtained using the SCREENS questionnaire [The use of four types of devices at home was considered as screen time: (1) television (including DVD, video games, PlayStation, and Xbox), (2) computers (desktop, laptop, and Chromebook), (3) telephones and smartphones, and (4) other mobile devices (tablets, iPad, and Nintendo Switch). For each device type, the weekday and weekend use times were averaged to obtain the device-specific screen time in hours per day, that is, ([total weekday × 5] + [total weekend day × 2]) / 7. The total screen time per day was calculated as the sum of use time for all 4 types of devices. To ensure the fidelity of the primary outcome in the questionnaire, the self-reported use time was cross-checked with screenshots of the screen media diary among 10% (18/180) of the participants. The request for the diary was made only after the completion of the final questionnaire. There was an agreement of 83% (15/18) between the reported time in the questionnaire and that in the diary. | PMC10196888 | ||
Secondary Outcome Measures | PMC10196888 | |||
Mother’s Knowledge | The items to measure parental knowledge were adapted from a previous study [ | PMC10196888 | ||
Mother’s Perception About the Influence of Screen Time on a Child’s Well-being | The total score for this outcome was calculated by averaging the responses to 11 items adapted from a previous study [ | PMC10196888 | ||
Mother’s Self-efficacy | Mother’s self-efficacy to reduce screen time was assessed using 9 items, 3 being adapted from the parenting self-efficacy scale used in the Infant Feeding Activity and Nutrition Trial [In addition, mothers’ self-efficacy to increase their child’s physical activity was measured using 8 items adapted from a previous study [ | PMC10196888 | ||
Mother’s Screen Time | Mothers’ weekday and weekend leisure screen time (excluding time spent on screen for work, school, or education purposes) was recorded in a way that is similar to recording the child’s screen time. | PMC10196888 | ||
Physical Household Environment | Parents were also required to report if digital devices were present in the child’s bedroom (“yes”=1 point and “no”=0 point) [ | PMC10196888 | ||
Data Collection | Data collection was performed between March 2021 and December 2021. Web links to self-administered questionnaires on Google Forms were disseminated through WhatsApp at 3 time points, namely, baseline, immediate after the intervention, and 3 months after the intervention. | PMC10196888 | ||
Data Analysis | Statistical analysis was conducted using SPSS software (version 27.0; IBM Corp). Normality was assessed using skewness and kurtosis. Mean and SD were calculated for continuous data, whereas frequency and percentage were computed for categorical data. The generalized linear mixed model (GLMM) was used to evaluate the effect of the intervention after adjusting for covariates (mother’s age, mother’s education, combined household income, child’s sex, and baseline scores). The models were also adjusted for the clustering effect at the school level. GLMM was run for each outcome. Each model had school as the random effect, whereas the fixed effects that were included were group, time, and interaction between group and time. The group × time interaction effect was the primary variable of interest in each model. The 95% CI was set for mean estimation, with a | PMC10196888 | ||
Ethics Approval | This study was approved by the Ethics Committee for Research Involving Human Subjects at University Putra Malaysia (JKEUPM-2020-284). Web-based consent was obtained from both representatives of the clusters (preschools) and individual participating mothers before randomization. All participants were free to withdraw from the study at any given time for any given reason, and they would not be replaced. No personal information was requested through the WhatsApp group, and their privacy and confidentiality were protected throughout the study. | PMC10196888 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.