Donor-derived cell-free DNA (dd-cfDNA) has been applied to monitor acute rejection (AR) in kidney and heart transplantation. This study was aimed to investigate the application of dd-cfDNA levels in the diagnosis of AR and chronic lung allograft dysfunction (CLAD) among the lung transplantation recipients (LTRs).One hundred and seventy LTRs were enrolled at the First Affiliated Hospital of Guangzhou Medical University between 1 June 2015 and 30 March 2021. Patients were divided into 4 groups: stable group, AR group, infection group and CLAD group. The level of dd-cfDNA was analyzed using target region sequencing and the performance characteristics of dd-cfDNA for diagnosis of AR and CLAD were determined, respectively.p < 0.001. Among them, the level of dd-cfDNA (%) was highest  in AR group, and higher in CLAD group , but lower in infection group  and lowest in stable group . AUC-ROC curve analysis showed that the threshold of dd-cfDNA for AR was 1.17%, with sensitivity being 89.19% and specificity being 86.47%, and the optimal threshold of 0.89% was determined of CLAD, with sensitivity being 95.00% and specificity of 76.99%.Kruskal–Wallis test showed that there were some significant differences in the level of dd-cfDNA (%) among the 4 groups, with Plasma dd-cfDNA could be a useful tool for the assessment of lung allograft rejection, including AR and CLAD, and holds promise as a noninvasive biomarker for “allograft injury” in both acute and chronic rejection following lung transplantation.The online version contains supplementary material available at 10.1186/s12890-022-02229-y. Lung transplantation, at present, is the only therapeutic option for patients with end-stage lung or pulmonary vascular disease. Lung transplantation has witnessed dramatic growth worldwide in the recent years; over 4,000 lung transplants are performed annually worldwide . NonetheCurrently, pathology from invasive biopsy tissue is the golden standard for diagnosis of AR and CLAD. Among the procedures commonly used to get the lung tissues, trans-bronchial lung biopsies (TBLBs) are the first choice. However, this approach is difficult to practice for most cases in clinical settings. Apart from the potential risks, cost-prohibitive burden, and inconvenience, it is always difficult to get a consent from the patients mainly because it is an invasive procedure; also, physicians may care about minimizing the development of secondary complications in relation to TBLB and may thus be unwilling to perform the procedure. Moreover, biopsies are costly, sampling-error prone, and also have restricted specificity and sensitivity, limited by subjective interpretation . Thus, aRecently, plasma donor derived cell-free DNA (dd-cfDNA) has become a hot topic in field of solid organ transplantation because emerging evidence suggests that detection of allograft injury via dd-cfDNA may be a noninvasive biomarker for allograft rejection –17. MoreA non-experimental retrospective cross-sectional study design was used in this work. This study adhered to the tenets of the Declaration of Helsinki and was approved by the ethics committee of the First Affiliate Hospital of Guangzhou Medical University (k2021-98). The informed consent was obtained from each recipient.https://dataview.ncbi.nlm.nih.gov/object/PRJNA801094?reviewer=vap7nq272jc2l86ligrr7clm3m (accession no. PRJNA801094). The inclusion criteria were as follows: 1) age ≥ 18 years; 2) single- or double-lung transplantation; 3) more than 14 days from the day of transplantation. The exclusion criteria were as follows: 1) incomplete medical data; 2) combined heart–lung transplantation or multi-organ transplantation; 3) “mixed diagnosis” of concurrent infection with rejection; 4) died from unknown causes.The recipients who had undergone lung transplantation at the First Affiliated Hospital of Guangzhou Medical University between 1 June 2015 and 30 March 2021 were screened. The recipients who underwent blood sample collection and dd-cfDNA testing were enrolled in our center from May 2020 to December 2021. The sequence data reported in this paper have been deposited in the Sequence Read Archive, Study cohorts were divided into 4 groups based on the final diagnosis which was determined by combining the clinical information and review of the treatment response. The study participants were divided into the following 4 groups: stable group (stable state without infection or rejection), AR group , infection group , and CLAD group (CLAD with or without risk factors).In the stable group, no symptoms were observed at the time of sample collection. In the infection group, the patients had some symptoms, which consisted of a new-onset cough or expectoration or aggravation of existing respiratory tract symptoms with or without purulent sputum, chest pain, dyspnea, hemoptysis, headache, fever, and rales on lung auscultation. In the AR group, the patients also had the similar symptoms mentioned above as in the infection group, and adventitious sounds on lung auscultation. In the CLAD group, most patients had decreased exercise capacity, shortness of breath, dyspnea (on exertion or at rest) to a varying degree, dry cough, or slight chest tightness that had persisted or progressed for at least 3 weeks.Data of study participants that were collected retrospectively, including demographic data, primary indication for lung transplantation, type of surgery , operation-related data, plasma cytomegalovirus (CMV) IgG status, CMV-DNA loads were record for both donor and recipients, induction treatment regimen, panel reactive antibody (PRA) and donor specific antibody (DSA) prior to and after the transplantation for the recipients, clinical information such as symptoms, signs, chest imaging findings such as X-ray or computed tomography (CT), laboratory routine tests, biochemical tests, tacrolimus trough levels, and etc.There were no opacities on the CT scans in the stable group. In the CLAD group, patients with BOS had air trapping/mosaic attenuation on their expiratory CT scan, whereas a common denominator in patients with restrictive allograft syndrome (RAS) was the presence of persistent pleuroparenchymal infiltrates on CT imaging.As part of our routine clinical protocol, all lung transplant recipients were treated with standardized triple immunosuppressive regimens comprising of calcineurin inhibitors (tacrolimus or cyclosporin A), mycophenolate mofetil, and prednisolone. Most patients were treated with basiliximab to induce immunosuppression.For dd-cfDNA detection, we specifically selected plasma samples more than 14-days posttransplant, to avoid the potential confounding complication of lung injury from ischemic-reperfusion of lung transplant operation. Plasma samples were associated with concurrent histopathologic diagnoses and bronchial-lavage fluid (BALF) microbiologic cultures. Samples that passed strict quality control from unique patients and had adequate plasma sample volume (2 mL) were analyzed with a clinical-grade NGS dd-cfDNA assay at a Chinese-certified Laboratory .A total of 6,200 human SNP loci were enriched by liquid hybridization, SNP loci selection criteria and bioinformatics protocol was conducted as reported in our previous study –21. In s. AMR was determined by the ISHLT and Banff Lung pathology working group criteria, which were consistent with “probable” AMR [The lung lobes with the most prominent lesions according to chest CT were selected for TBLB with fiberoptic bronchoscopy by using standardized procedures. Histopathology for TBLB specimens were evaluated by two experienced pathologists according to the Revised International Society of Heart and Lung Transplant (ISHLT) working group recommendations . In addible” AMR . BOS wasble” AMR , 25. Theble” AMR , biochemble” AMR , 28. Thep-level less than 0.05 is considered a significant difference.All analyses were performed in IBM SPSS Statistics (V.22). Graphs were created using GraphPad Prism 8 for Windows. Descriptive statistics are used to describe the LTRs demographics and distribution of dd-cfDNA measurements obtained from blood samples. Non-parametric distributions were compared using the Wilcoxon rank sum test (two groups), and the Kruskal–Wallis rank sum test (multiple groups). Post-hoc analysis for the latter was performed using Dunn’s test with Bonferroni adjustment. Paired t test was used to compare the change rate of FEV1%pred. Spearman's rank correlation was used to assess relationships between dd-cfDNA (%) and the rate of lung function change. A receiver operating characteristic curve (ROC) analysis was performed to assess how well dd-cfDNA fraction (%) discriminated among different subgroup. A threshold was established to categorize dd-cfDNA scores indicating AR, CLAD or demonstrating stable or infection based upon the distribution of the data. All statistical analyses were two-tailed, and Excluding 14 blood samples from 12 recipients whose information was unsuitable for this study, 191 blood samples from 170 LTRs were included in this study. Among them, 151 blood samples were collected from 151 recipients, 36 from 18 recipients , and four from one recipient . Figure p = 0.322 and 0.254, respectively).The demographics of the study recipients who were stratified and divided into groups at the time of diagnosis were shown in Table p < 0.001  among the 4 groups, with 001 Fig. . Among tp = 0.990), with the level of dd-cfDNA (%) being  in LTRs with single lung transplantation and  in those with bilateral lung transplantation.The Kruskal–Wallis test showed that there was no significant difference between LTRs with single- or bilateral lung transplantation in the stable group , where the optimal threshold of 1.17% was determined for AR  of the receiver operator characteristics (ROC) analysis was applied to evaluate the performance of the dd-cfDNA (%) levels in diagnosing AR and CLAD, respectively. The ROC curve demonstrated 0.929 , where the optimal threshold of 0.89% was determined for dd-cfDNA. At this cutoff, sensitivity for CLAD was 95%  and specificity was 76.99% , with PPV of 42.2%  and NPV of 98.8% .Figure p = 0.001) among the patients. The levels of dd-cfDNA were significantly decreased after the treatment, with the levels down below the cut-off level of 1.17% in ten of the patients who underwent AR treatment. At the same time, the clinical symptom for AR was relapsed  detected repeatedly, with 18 recipients detected twice at different period of post-transplant time and one recipient detected longitudinally 4 times at specified intervals post-transplant. Among the 18 recipients, 14 were diagnosed with AR, 2 with CLAD, and 3 with infection. Paired t test demonstrated that there was significant difference in dd-cfDNA (%) before and after the treatment . Post-hoc analysis showed that there were significant differences in the change rate of FEV1%pred among the four groups . Spearman correlation analysis showed that the change rate of FEV1%pred was significantly correlated with the level of dd-cfDNA (%) in AR group  levels among the 4 groups, with the highest level in AR group. The ROC curve demonstrated an AUC of 0.929, where the optimal threshold of 1.17% was determined for AR, with the sensitivity for AR diagnosis been 89.19% . The study design and result of this investigation were very similar to that by Kiran et al. , but in The other alternative explanation could be attributed to the limited sample size in both studies. Nevertheless, in this study, we suggest employing plasma dd-cfDNA (%) as a non-invasive biomarker for the clinical diagnosis of AR. This suggestion can be supported by growing number of recent studies in lung transplantation , 31 and Moreover, Wilcoxon rank sum tests for cohorts with CLAD showed a significantly elevated dd-cfDNA (%) level compared with the stable cohort. AUC-ROC of the dd-cfDNA value (%) was applied to discriminate CLAD from CLAD-free cohort, which demonstrated an AUC of 0.874, where the optimal threshold of 0.89%, with the sensitivity of 95% and specificity of 76.99% . The result presented in this study was consistent with those of recent studies –32, 34 aMoreover, we observed that the elevated dd-cfDNA level at initial stage of the AR episode was lowered gradually with the treatment against AR in one patient who had been diagnosed of AR. By detecting of dd-cfDNA levels repeatedly, before and after the clinically-based treatment, the study found that the elevated dd-cfDNA levels were significantly lowered down following the treatment Fig. A. In addThe dd-cfDNA level for the cohort with respiratory allograft infection in the absence of concurrent rejection was significantly lowered when compared to the AR and CLAD cohort, and it was slightly elevated when compared with stable healthy cohort, although it did not achieve statistical significance. The study result was in agreement with that of Kiran et al. , which aIn order explore the association of plasma dd-cfDNA level with the other non-invasive index for allograft injury, we analyzed its correlation with lung function. The results showed that there was a significant negative correlation between plasma dd-cfDNA level and FEV1% pred change rate in AR group. The results were expected because allograft function should be decreased with the occurrence of injury (AR). Level of dd-cfDNA has no significant correlation with FEV1% change rate in CLAD group. Because multiple factors contribute to CLAD, including alloantigen-dependent (cellular and antibody-mediated rejection) and alloantigen-independent factors . Increase level of dd-cfDNA main related to alloantigen-dependent allograft-injury. However, lung function is not a specific index, as pulmonary function decreases in many kinds of pulmonary complications among LTRs. Our study results suggest that plasma dd-cfDNA is an interesting biomarker of rejection (including acute and chronic rejections), which has a much higher specificity than lung function in diagnosing of allograft rejection.Collectively, our study results, for the first time, showed interesting findings in Chinese lung transplantation by using a total of 6,200 human SNP loci to select and detect. Compared to other already available cf-ddDNA kits (Multiplex PCR based sequencing) such as Alloseq or AlloSure, our method can obtain more effective SNP loci suitable for Chinese population to ensure the accuracy of dd-cfDNA test. Multiplex PCR based sequencing methods cannot remove PCR duplicate, thus, many SNPs were employed in our study for the following reasons: 1) dd-cfDNA quantification is affected because of PCR bias; 2) The effective depth of sequencing is not known, and the limit of detection (LOD) cannot be accurately evaluated; 3) The ability to remove the wrong base of sequencing or PCR error is limited; 4) the limit of blank (LOB) is high.It should be noted that the present study has a few limitations. First, it was a single center study with a limited sample size, and a larger multicenter study is needed in China to accurately evaluate the diagnostic value of plasma dd-cfDNA in diagnosing rejection in lung transplantation. Second, this was a cross-sectional study in which samples were randomly collected from some patients randomly. Due to the high cost of dd-cfDNA assay, no longitudinal comparison was performed on schedule. However, dd-cfDNA detection should be conducted before and after the treatment to confirm the diagnostic value of dd-cfDNA during active allograft rejection in lung transplant recipients. A prospectively designed study should be performed in order to help clinician develop intervention strategies for CLAD at the early stage. Third, BALF should be a good sample to study, as the level of dd-cfDNA in BALF might provide researchers with more information when combined with the level in plasma. A further study on dd-cfDNA in BALF is now ongoing which will be reported in the near future. Finally, lung biopsy was not available from every participant in this study, thus there might be some bias in the clinical diagnosis. However, treatment response helped a lot when the study initiated and the clinical information was checked and reviewed.In conclusion, plasma dd-cfDNA is significantly elevated in patients with AR and CLAD following lung transplantation, and it is more prominent during the period of AR. Plasma dd-cfDNA assessment therefore holds promise as a noninvasive biomarker for early detection of lung allograft injuries including AR and CLAD, with a high sensitivity and specificity.Additional file 1: Figure S1. Thoracic computed tomography (CT) images from a right single lung transplant recipient during different period post lung transplantation.Additional file 2: Figure S2. Thoracic CT images show multiple infiltration in the right allograft lung during the period of the acute exacerbation.Additional file 3: Figure S3. Thoracic CT images during the recovery stage of the acute exacerbation.Additional file 4: Table S1. Information on the infectious agents isolated from BALF in the AR group.Additional file 5: Table S2. Information on the infectious agents isolated from BALF in the infection group.


We characterize the overall incidence and risk factors for breakthrough infection among fully vaccinated participants in the North Carolina COVID-19 Community Research Partnership cohort. Among 15,808 eligible participants, 638 reported a positive SARS-CoV-2 test after vaccination. Factors associated with a lower risk of breakthrough in the time-to-event analysis included older age, prior SARS-CovV-2 infection, higher rates of face mask use, and receipt of a booster vaccination. Higher rates of breakthrough were reported by participants vaccinated with BNT162b2 or Ad26.COV2.S compared to mRNA-1273, in suburban or rural counties compared to urban counties, and during circulation of the Delta and Omicron variants. While COVID-19 vaccines prevent or attenuate the severity of SARS-CoV-2 infection, little is known about risk factors for breakthrough infection .http://www.covid19communitystudy.org/, 30 September 2022). The participating study sites invited participants from inside and outside their healthcare systems via email and patient portal messaging, study websites, and during community outreach events. This study was approved by the Wake Forest School of Medicine Institutional Review Board. The analysis includes data through 3 January 2022.The NC CCRP is an observational cohort study assessing COVID-19 symptoms, test results, vaccination status, and risk behavior via daily email or text surveys. Adults 18 years and older were enrolled between 13 April 2020 and 14 August 2021 at six NC healthcare systems , and periodic short supplementary surveys. Demographic data, including age, race/ethnicity, healthcare worker status, and COVID-19 infection prior to enrollment, and address were collected at enrollment. Counties of residence were classified as urban, suburban, or rural based on average population density per square mile as calculated by the NC Rural Center based on the 2020 U.S. Census . PotentiWe defined SARS-CoV-2 vaccination as participant self-report of receiving two doses of either the Pfizer BioNTech BNT162b2 or Moderna mRNA-1273 vaccine, or one dose of the Janssen non-replicating viral vector vaccine Ad26.COV2.S. Vaccination status was confirmed for the subset of participants with accessible EHR data [In the current analysis, the primary outcome was weeks until the first self-reported infection (positive SARS-CoV-2 antigen or nucleic acid amplification test) occurring ≥14 days after full vaccination. Participants were able to self-report test results from any COVID-19 viral test they took as part of their work, social life, or after developing symptoms, including tests that were conducted at a testing center. Time to breakthrough was defined as time from full vaccination to first self-reported infection. Participants were censored if they withdrew from the study, at the date of their last status update, or at the end of the analysis period on 3 January 2022.Time-varying covariates were incorporated on a participant by calendar week basis. The vaccination proportion in the county of residence by calendar week was estimated as the cumulative number of “full” vaccination doses up to that calendar week , dividedNearly 80% of the cohort reported at least once per calendar week for all the weeks of their follow-up. Two participants with missing sex and participants with vaccine brand other than Janssen, Pfizer, and Moderna were excluded from the analysis. Participants who did not specify their race/ethnicity at enrollment were classified as “Non-Hispanic Other”. Participants who did not indicate that they consider themselves healthcare workers were considered non-healthcare workers. Participants who did not complete a daily survey in a calendar week were considered to have used a face mask < 90% of the time.p-values were calculated. p-values lower than 5% were considered significant. All analyses used R version 4.0.3 [Cox proportional hazards models with fixed and time-varying covariates were used to estimate hazard rates. Univariate and multivariate models were run, with all variables assessed in the univariate models included in the multivariate model. Event rates were calculated as the total number of events divided by one hundredth the total duration of follow-up of all participants in the cohort. Time to event was modeled using Cox proportional hazards models using robust variance estimates to account for data clustered by participant . Only maon 4.0.3 .Study population characteristics are summarized in Median and interquartile follow-up times following full vaccination were 29.3 interquartile range (IQR = 21.7–42.7) weeks among infected participants and 31.6 (IQR = 21.7–36.6) weeks among uninfected participants. The cumulative incidence of breakthrough infection was 6.95% over 45 weeks of follow-up following full vaccination . While tIn the multivariable analysis , age 45 When the multivariable analysis was stratified by age , breakthAmong vaccinated individuals, the magnitude of risk for breakthrough infection and possible strategies to mitigate that risk are of great importance. The rate of breakthrough infections increased over time, consistent with increasing community spread in concert with waning vaccine effectiveness. Our data support previous reports of higher effectiveness of Moderna mRNA-1273 relative to Pfizer/BNT BNT162b2 ,12, and The daily survey responses capture whether a test was conducted and the result of the test, but does not capture the detail of where, how, or why the test was performed. Naturally, this type of self-directed testing that does not follow a pre-described testing schedule is more likely to detect symptomatic infections and under-detect asymptomatic infections. Moreover, participants may take tests and fail to report them in the system, which may happen more often with negative tests. In weeks when participants did not have any status update, including no self-reported infection, infections were treated as absent, likely resulting in an underestimation of the incidence of SARS-CoV-2 infection.In any observational study, there are significant limitations related to bias or residual confounding, generalizability, and power such that results should be interpreted with caution. In addition, our cohort includes a large proportion of healthcare workers and there may be important differences among this group compared with the general population with regard to study interest and engagement, exposure profiles, and risk mitigation behaviors. This degree of oversampling of healthcare workers was not intentional, but rather the likely result of the fact that enrollment was based at large healthcare systems. Furthermore, the difference in vaccination release dates was not accounted for in the models. Nevertheless, many of our findings corroborate the work of others, supporting the validity of the data.In summary, this real-world analysis adds to the understanding of risk factors associated with breakthrough SARS-CoV-2 infections and highlights opportunities for mitigation. Specifically, the lower rates of breakthrough infection associated with face mask use and receipt of a booster highlight specific measures that individuals can take to minimize their risk for COVID-19.


Surveillance systems are important in detecting changes in disease patterns and can act as early warning systems for emerging disease outbreaks. We hypothesized that analysis of data from existing global influenza surveillance networks early in the COVID-19 pandemic could identify outliers in influenza-negative influenza-like illness (ILI). We used data-driven methods to detect outliers in ILI that preceded the first reported peaks of COVID-19.We used data from the World Health Organization’s Global Influenza Surveillance and Response System to evaluate time series outliers in influenza-negative ILI. Using automated autoregressive integrated moving average (ARIMA) time series outlier detection models and baseline influenza-negative ILI training data from 2015–2019, we analyzed 8,792 country-weeks across 28 countries to identify the first week in 2020 with a positive outlier in influenza-negative ILI. We present the difference in weeks between identified outliers and the first reported COVID-19 peaks in these 28 countries with high levels of data completeness for influenza surveillance data and the highest number of reported COVID-19 cases globally in 2020. To account for missing data, we also performed a sensitivity analysis using linear interpolation for missing observations of influenza-negative ILI. In 16 of the 28 countries (57%) included in this study, we identified positive outliers in cases of influenza-negative ILI that predated the first reported COVID-19 peak in each country; the average lag between the first positive ILI outlier and the reported COVID-19 peak was 13.3 weeks (standard deviation 6.8). In our primary analysis, the earliest outliers occurred during the week of January 13, 2020, in Peru, the Philippines, Poland, and Spain. Using linear interpolation for missing data, the earliest outliers were detected during the weeks beginning December 30, 2019, and January 20, 2020, in Poland and Peru, respectively. This contrasts with the reported COVID-19 peaks, which occurred on April 6 in Poland and June 1 in Peru. In many low- and middle-income countries in particular, the lag between detected outliers and COVID-19 peaks exceeded 12 weeks. These outliers may represent undetected spread of SARS-CoV-2, although a limitation of this study is that we could not evaluate SARS-CoV-2 positivity.Using an automated system of influenza-negative ILI outlier monitoring may have informed countries of the spread of COVID-19 more than 13 weeks before the first reported COVID-19 peaks. This proof-of-concept paper suggests that a system of influenza-negative ILI outlier monitoring could have informed national and global responses to SARS-CoV-2 during the rapid spread of this novel pathogen in early 2020. Natalie L Cobb and colleagues use routine influenza surveillance data to detect outliers in influenza-like-illness during the COVID-19 pandemic. Early detection of respiratory viral outbreaks, such as SARS-CoV-2, is key for public health response and mitigation measures.In this study, we used routine influenza surveillance data to detect outliers in influenza-like illness (ILI) during the COVID-19 pandemic that could suggest spread of SARS-CoV-2.We hypothesized that using data-driven methods would identify increased case counts of influenza-negative ILI prior to reported peaks of COVID-19.We used routine influenza surveillance data from the World Health Organization’s FluNet and applied automated outlier detection methods to identify outliers in influenza-negative ILI in 2020 across 28 countries.In 16 countries, we detected outliers that preceded the first reported COVID-19 peaks, with an average lag time of 13.3 weeks.In 7 countries, the week of the first outlier changed when accounting for missing data in the models.This study serves as a proof of concept and suggests a potential role for the use of automated data monitoring and outlier detection systems to identify outbreaks in respiratory viral illness.These findings also highlight the importance of strengthening routine disease surveillance networks to enhance our ability to identify novel diseases and inform public health responses on a global scale. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported from a cluster of pneumonia patients in Wuhan, China, during late December 2019 . During Leveraging existing and long-running influenza surveillance systems may provide insight into the early spread of SARS-CoV-2 globally and serve to enhance monitoring for emerging non-influenza respiratory viral pathogens. The WHO Global Influenza Surveillance and Response System (GISRS) is a network comprising national influenza centers and WHO collaborating centers and laboratories across 123 WHO member states that collect respiratory specimens for laboratory influenza testing . SamplesIn this study, we evaluate outliers in influenza-negative ILI in 2020 compared to trends over the previous 5 years among countries with established ILI surveillance systems and a high incidence of COVID-19. We hypothesized that automated outlier detection methods would detect outliers in influenza-negative ILI during 2020 that preceded the first peaks of SARS-CoV-2. This study is intended as a proof of concept for the use of continuous automated global detection of influenza-negative ILI outliers as a potential early warning system for novel circulating viral pathogens, which could be especially vital for LMICs, which often have limited access to the rapid development and deployment of diagnostic tests for novel viral pathogens such as SARS-CoV-2.All data were obtained from publicly available sources. Weekly and cumulative COVID-19 cases by country were obtained from the WHO COVID-19 dashboard . Data foTo ensure a representative sample of countries across income groups, we selected the top 40 countries with highest cumulative number of COVID-19 cases through January 3, 2021 (ISO week 53), stratified by World Bank income classification , which are listed in To identify the first COVID-19 peak in each country, we evaluated graphs of weekly COVID-19 cases from the WHO data. The peak was defined as the first week with the highest number of cases within a period of rising cases followed by a decrease or plateau over a duration of at least 3 weeks. The minimum threshold for a peak was at least 100 cases per week.Data for weekly cases of influenza-negative ILI were abstracted as reported in FluNet. Cases are reported in absolute values. If influenza-negative ILI was not reported, a value was calculated according to the weekly number of specimens processed minus the weekly number of influenza-positive specimens. Values less than 0 were considered erroneous and treated as missing data.The aim of this study was to identify positive outliers in influenza-negative ILI during the first year of the COVID-19 pandemic using automated data-driven time series methods. Our a priori analysis plan included (1) stratifying countries by income group and identifying the countries with the highest number of COVID-19 cases in 2020, (2) exploring missing data and excluding countries with high levels of missingness, (3) utilizing automated outlier detection methods to identify positive outliers in influenza-negative ILI during 2020, (4) evaluating the time difference between detected ILI outliers and reported COVID-19 peaks, and (5) performing a sensitivity analysis using interpolation for missing data. To address comments during peer review, we subsequently performed model fit diagnostics to evaluate the autocorrelation of residuals for each fitted model.Descriptive statistics, including the median weekly influenza-negative ILI case counts, are reported by World Bank income classification. To identify outliers in time series trends, we used a data-driven approach based on autoregressive integrated moving average (ARIMA) modeling with the “tsoutliers” package in R . The “tsAmong the 28 countries included in this study, 4.7%  of observations for influenza-negative ILI were missing. The number of missing observations by country is provided in We detected positive outliers during 2020 in 19 countries 68%). In 6 countries , no positive outliers were detected during 2020, and in 3 countries , outlier analysis was limited by model non-convergence. For the 19 countries in which a positive outlier was detected, the outlier predated the first reported COVID-19 peak in 16 countries (84%) . In 3 co%. In 6 cThe earliest outliers occurred during the week of January 13, 2020, in Peru, the Philippines, Poland, and Spain. Among the countries with positive outliers that predated the first reported COVID-19 peak, time series outliers were detected on average 13.3 weeks prior to the reported COVID-19 peak (standard deviation 6.8). Seven countries demonstrated a lag between the first detected outlier and reported COVID-19 peak of greater than 12 weeks . In 2 countries, the lag time was 4 or fewer weeks (France and the United States).Using linear interpolation for missing data Model 2; , the weep-value less than 0.05, indicating potential issues with model fit: Afghanistan, Bangladesh, Colombia, Indonesia, Spain, and the United States  and 20 weeks before the first COVID-19 peak . In many LMICs, including Bolivia, Colombia, and Mozambique, the first outlier occurred near the time of the first reported COVID-19 case and several weeks prior to the first peak. The observed lag times are likely impacted by both the robustness of public health reporting structures as well as local policies. For instance, limited availability of testing early in the pandemic may have resulted in underreporting of cases and delayed policy measures. Estimates of excess mortality for COVID-19 have suggested that the number of cumulative deaths was much higher than the number of reported deaths in many LMICs, including India, Russia, Mexico, Brazil, Indonesia, and Pakistan .In 3 countries , the first detected outlier in 2020 occurred after the first reported COVID-19 peak. There are likely several contributing factors. For instance in Uganda, the relatively small size of the first COVID-19 wave and limited local transmission may have resulted in fewer cases in routine surveillance . In Madaz-scores preceded a rise in COVID-19 cases or deaths with a 2-week lag, which was attributed to the course of disease and testing delays [In previous single-country studies, influenza surveillance systems have been used to detect surges in ILI during the pandemic ,10,28, ag delays . DespiteWhile we cannot definitively conclude from our analysis that non-influenza ILI outliers were caused by undetected cases of SARS-CoV-2, our findings suggest that early community transmission of SARS-CoV-2 may have been underestimated in several countries. Alternatively, outliers may also reflect changes in case reporting or patterns in individuals seeking care for respiratory illness, particularly after a pandemic was declared. Disruptions to routine surveillance, due to the pandemic or other factors, may also impact these findings. For instance, in Mozambique, armed conflicts and displacements may have resulted in disruptions to disease surveillance . The ideThere are several additional limitations to this study. First, a key assumption of ARIMA modeling is that the data are stationary, with a constant mean and variance. While differencing is conducted to achieve stationarity during the automated ARIMA process, some countries may continue to exhibit non-stationarity. In our model diagnostics, residuals from 6 countries demonstrated ongoing autocorrelation after model fit . If thisDespite these limitations, the use of data-driven approaches for outlier detection in routine surveillance systems may have broad applicability in the future. A major strength of this study is the use of automated ARIMA modeling, which allows for differences in temporal and seasonal patterns by country. Integrating automated outlier detection systems within surveillance networks and establishing multi-pathogen testing sites may be beneficial in detecting novel disease outbreaks. While data quality and data missingness are significant challenges, this study emphasizes the importance of strengthening reporting and data quality to maximize the public health impact of these routine surveillance systems. While we restricted the analysis in this study to countries with limited missing data, in our sensitivity analysis, the timing of identified outliers changed in 7 countries when we incorporated interpolated data into the models. Improving data quality and completeness for respiratory surveillance systems would likely enhance the feasibility of using data-driven approaches to detect deviations in trends over time.In summary, this study demonstrates a potential role for automated outlier detection in the identification and monitoring of novel respiratory pathogens using influenza surveillance networks. During the first year of the COVID-19 pandemic, we found outliers in influenza-negative ILI for 16 countries that preceded reported COVID-19 peaks and, in some countries, the first reported COVID-19 case. In many LMICs the lag between the first outlier and the COVID-19 peak exceeded 12 weeks, which may be related to challenges in diagnostic testing, reporting, and public health responses during the early stages of the COVID-19 pandemic. Developing and improving existing respiratory disease surveillance networks will be essential for improving our response to future pandemics and limiting morbidity and mortality globally. An automated outlier detection system in respiratory disease surveillance could facilitate early identification of novel pathogens and inform public health responses including implementing multi-pathogen diagnostic testing, and enacting policies to mitigate the impact of disease outbreaks.S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S4 Fig(DOCX)Click here for additional data file.S5 Fig(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.S3 Text(DOCX)Click here for additional data file.


In this cross-sectional study, we aimed to evaluate the factors associated with psoriasis symptom worsening and impaired quality of life (QoL) in individuals with psoriasis during the COVID-19 pandemic lockdown.During the second COVID-19 national lockdown (January–April 2021) in Lithuania, individuals diagnosed with psoriasis were invited to fill in an anonymous online survey including sociodemographic and life-style factors, psoriasis-related clinical symptoms, the Dermatology Life Quality Index (DLQI) and the Patients' Health Questionnaire (PHQ).p = 0.004) and decreased income . The strongest predictor of impaired QoL was male sex . Contribution of specific depressive symptoms was evident for both models.A total of 297 respondents completed the survey. The majority of them (52.5%) reported worsened clinical symptoms of psoriasis during the COVID-19 lockdown period. In total, 43.1% of responders reported significant depressive symptoms (PHQ-9 ≥ 10) and 23.6% reported impaired disease-related QoL (DLQI > 10). The strongest predictor of psoriasis symptoms worsening was the need for changes in psoriasis treatment, with an odds ratio (OR) of 2.73 (95% CI 1.37–5.44, Worsening of psoriasis symptoms during the COVID-19 lockdown was associated with decreased income, psoriasis treatment changes and depression symptoms. Impaired QoL was associated with male sex, symptom worsening and depression. Specific depression symptoms may have contributed to more symptom worsening and impaired QoL than the depressive symptomatology as a whole. Coronavirus disease 2019 (COVID-19) outbreak, with lockdown periods and strict quarantine requirements, and the fear of being infected and transmitting the disease, led to significant life style changes, that were associated with psychological distress and the risk of deterioration of mental health –5. OveraPsoriasis is a chronic, papulosquamous, multisystem inflammatory skin disease  with a pPsoriasis is a benign disease, and as such does not affect patients' survival; however, it has a profound impact on individuals' disease-related QoL . PreviouThe COVID-19 pandemic posed as an additional stressor for individuals with psoriasis, and a number of factors associated with the burden of the pandemic may have contributed to the worsening of disease symptoms and impaired QoL. For example, changes in family status during the COVID-19 pandemic may have affected individuals' ability to cope with stress, as having a significant other may have acted as a form of support during difficult times, thus preventing disease symptoms from worsening or QoL impairment. Education has been shown to be a protective factor for impaired QoL; however, it is unlikely that this factor directly contributed to disease symptom worsening. Specific factors associated with COVID-19 posed changes such as physical isolation, higher intensity of work load, and reduced income may have contributed to symptom worsening and impaired QoL. These factors have been shown to greatly contribute to mental distress, mainly depression, associated with the COVID-19 pandemic . FurtherWe designed a study that allowed us to investigate the factors contributing to disease symptom worsening and impaired QoL in individuals with psoriasis during the COVID-19 pandemic lockdown. We expected that younger age and female sex would be associated with both disease symptom severity and impaired QoL. However, we expected that various aspects of patients' lives, including lower education levels, decreased income, relationships and other previously-identified risk factors  would bep > 0.05). Otherwise, there were no missing data in our dataset and the remaining sample of 297 was comprised of the individuals who fully completed the questionnaire. However, the engagement rate for accessing the questionnaire was not monitored.Adult (over 18 years) subjects with a psoriasis diagnosis were invited to participate in this study and fill in an anonymous online survey. Information about the study and an invitation for participation was provided by the study researchers, sharing information about the study and the link to the online survey to primary care physicians and to a number of psoriasis patient social media groups. Inclusion criteria for the study were: adult (over 18 years old) subjects with a diagnosis of any type of psoriasis at any time during their life. This cross-sectional study was conducted between January and April 2021, during the second COVID-19 lockdown period in Lithuania. The study procedures were approved by the Bioethics Center of the of Lithuanian University of Health Sciences -19, January 21, 2021). Before starting the survey, participants had to provide online informed consent to participate in the study by ticking the appropriate answer “agree/disagree.” Of the 306 respondents who accepted the invitation and completed the survey, data from nine surveys were excluded from the final analysis due to not having a confirmed clinical diagnosis of psoriasis. There were no significant differences among the included and excluded subjects in terms of age or sex  and changes in mental health symptoms, and initiation or change in psychotropic medications and/or psychotherapeutic interventions during the COVID-19 lockdown period. The psoriasis symptom worsening was assessed using a single question “During the COVID-19 pandemic (since approximately March 2020), have the symptoms caused by psoriasis changed” with possible answer ranging from “0” “symptoms got better” to “5” “significantly worsened symptoms”. More information about questions provided for the study participants can be found in the In the next two parts of the evaluation, two standardized questionnaires were used: the Dermatology Life Quality Index (DLQI)  and the The DLQI questionnaire is the first dermatological QoL questionnaire, published in 1994 . This quThe PHQ-9 is a brief self-rated questionnaire, which is part of the PHQ for the assessment of the severity of depressive symptoms during the past 2 weeks. The questionnaire consists of nine items that fit the Diagnostic and Statistical Manual-IV diagnostic criteria for major depressive disorder , 35. ForU test were used to examine the continuous variables, and chi-square tests were used to test the categorical variables.The data were analyzed with SPSS Version 27.0.0 . Mann-Whitney The differences in sociodemographic, clinical and life-style factors, and mental distress symptoms reported by individuals who experienced worsened psoriasis symptoms and those who did not experience any change in symptoms were assessed. Mann-Whitney U test were applied to compare PHQ-9 and DLQI scores, and chi-square tests were used for comparisons in terms of sex, family status, education, activity in relation to the COVID-19 lockdown, intensity of workload, income, duration of psoriasis, treatment of psoriasis, the need for changes in psoriasis treatment during the COVID-19 lockdown, and whether they had to seek psychological/psychotherapeutic help. The same comparisons were later performed in individuals who reported impaired disease-related QoL (threshold score of DLQI > 10) vs. individuals with psoriasis who experienced only mild impairment in their health-related QoL (DLQI ≤ 10) during the COVID-19 pandemic. This comparative analysis was conducted in order to investigate possible significant differences between the two groups and identify those variables that might play a role in psoriasis symptom worsening and impaired QoL during the COVID-19 pandemic.Two separate logistic regression analyses were then performed to investigate associations between sociodemographic factors, life-style factors and mental distress symptoms, and worsened psoriasis symptoms and impaired health-related QoL. The response variable for the first regression model was worsened psoriasis symptoms , whereas, for the second regression model, the response variable was health-related QoL ” or 1, “moderate-to-severe impairment of QoL (DLQI > 10)”.At the final stage, we performed logistic regression analyses (stepwise method) to determine whether specific PHQ-9 items predicted psoriasis symptom worsening and impaired QoL more precisely compared to the total score of the scale.n = 232; 78.1%). Most of the sample were highly educated, with at least a bachelor's degree (>15 years of studies) , and with stable or increased income during the pandemic . A considerable number of individuals reported over 5 years of history of psoriasis , and most of the participants were receiving topical treatment  including direct application of topical drugs onto skin rashes .The final sample comprised 297 individuals with psoriasis who completed the survey. n = 128; 43.1%). Impaired disease-related QoL was reported by a smaller number of individuals .A total of 52 (17.5%) individuals reported starting use of psychotropic medications or increasing their dosage and 31 (10.4%) individuals reported seeking psychological/psychotherapeutic help during the COVID-19 pandemic. Almost half of the individuals responding to the survey reported significant depression symptoms  = 8.84, p = 0.003; N = 156], with a greater proportion of respondents with limited activity or self-isolation  reporting worsened symptoms compared to those with unlimited activity .Decreased activity in relation to the COVID-19 lockdown was found among those who reported worsened psoriasis symptoms , together with the need for changes in psoriasis treatment during the COVID-19 lockdown , and starting the use of psychotropic medications or increasing their dosage .Decreased income was also among the factors related to worsened psoriasis symptoms .The DLQI scores were also significantly higher in individuals with worsened psoriasis symptoms  in comparison to individuals who reported no such changes , .N = 297) = 8.24, p < 0.004; N = 70], with a greater proportion of female  than male  participants reporting QoL impairment.A sex difference was found among those who reported impaired QoL , needed to seek psychological/psychotherapeutic help , and who had a higher severity of depressive symptoms .The group with impaired disease-related QoL (based on the DLQI threshold score of >10) comprised a higher number of individuals who needed to change psoriasis treatment during the COVID-19 lockdown . The patients/participants provided their written informed consent to participate in this study.JB and VS: designed the study. MS: collected and analyzed the data. AP: statistical analyses. JB, MS, AP, and VS: drafted and edited the manuscript. All authors contributed to the manuscript and approved the final version.


The advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its consequent illness, coronavirus disease 2019 (COVID-19), has revealed the severe impact of new, contagious pathogens on the population throughout the globe. Here, we describe the fundamental notions of herd immunity and discuss their consequences from the perspective of COVID-19, along with the obstacles to acquiring herd immunity. SARS-CoV-2 causes COVID-19, a contagious respiratory infection. It is a major global health issue, with more than 179 million positive cases and 3.8 million deaths globally. It has impacted more than 159 countries; hence, the World Health Organization designated it a pandemic. Different vaccines have been developed against coronavirus to slow the spread of this deadly virus. Immunizing people against coronavirus is the key to getting through this infectious virus. The central concept of this review article is the effect of vaccinating a large population to achieve herd immunity and the reasons for the delay in developing herd immunity. Herd immunity can prove highly beneficial for dealing with reinfection. Moreover, it can reduce the severity of the reinfection in many people who are twice infected with COVID-19. Herd immunity can prevent people in the high-risk group such as immunocompromised individuals; those on immunosuppressants; organ transplant recipients; particular age groups such as neonates, infants, toddlers, and elderly; those with impaired immunity; those with anaphylaxis reactions; and people with chronic diseases. However, due to repeated mutations of the virus, it is evolving into new strains with more severity. Its consequences on the immune system and response to a vaccine are still a big challenge to overcome. How new variants of COVID-19 impacted herd immunity needs to be investigated. The duration required for the development of herd immunity and how long it would last is still under research, along with the number of doses needed, booster doses, and the proportion of the population to be vaccinated. The recent global pandemic, coronavirus disease 2019 (COVID-19), caused by the highly virulent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is extremely contagious, rapidly spreading, and is the cardinal cause of increased morbidity and mortality rates worldwide . Herd imMethodologyWe performed a systematic search through PubMed and PubMed Central in August 2022 using keywords such as “covid-19” and “herd immunity” (((covid-19 [Title/Abstract]) OR (coronavirus [Title/Abstract])) OR (mutation*[Title/Abstract])) OR (“covid-19” [MeSH Terms]) AND ((“herd immunity” [Title/Abstract]) OR (immunocompromised [Title/Abstract])) OR (“herd immunity” [MeSH Terms]). We additionally searched for key references from the bibliographies of the relevant studies. The search was updated in October 2022.One reviewer independently monitored the retrieved studies against the inclusion criteria based on the title and abstract and then on full texts. Another reviewer also reviewed approximately 20% of these studies to validate the inclusion of studies. Data were extracted and tabulated. Details about the percentage of the population vaccinated with single, double, and booster doses and some variants of the COVID-19 study were tabulated. Figure 0, which refers to the average number of secondary infections caused by an infected person. Consider a hypothetical pathogen with an R0 of 4, on average, one infected person will infect four others during the exposure, assuming no immunity exists in the population. Mathematically, the herd immunity threshold is defined by 1 - 1/R0, and R0 is directly proportional to the contagious tendency of COVID-19 [Herd immunity, also called community immunity, is when a significant fraction of the population is immune to a specific pathogen and develops resistance against a particular virus or bacteria, following which the infection rate falls, and the disease dwindles . It can COVID-19 . For a mCOVID-19 . If the COVID-19 . AntivirCOVID-19 . AccordiCOVID-19 . Table 1COVID-19 .The effect of the number of vaccine doses and booster doses on herd immunity, according to some researchers, takes at least six months to develop immunity after administering a vaccine, and the duration up to which immunity will last remains unknown .Major hurdles in acquiring herd immunityVaccine-hesitant people are not getting vaccinated because they fear their hazardous effects, and some have religious beliefs regarding COVID-19. There is much fake news about COVID-19 vaccines on various social media platforms. Some people blindly follow it and spread it in their community . People COVID-19: vaccine allergy and effects on immunocompromised peopleHerd immunity against COVID-19 can rescue people who suffer from allergies to COVID-19 vaccines. In these people, taking the vaccine can cause anaphylaxis, polyethylene glycol allergy, and polysorbate allergy . COVID-1ImmunologyThe determination of the SARS-CoV-2 immunological memory state aids in the identification of reinfection risk and vaccination efficacy . As a reThe first-generation COVID-19 vaccinations were potent in preventing acute illness and hospitalization. Still, recurrent episodes of infections are associated with SARS-CoV-2 variants that exhibit an increased ability to evade antibodies, resulting in decreased vaccine effectiveness . EvasiveRapid population immunity by vaccinating a large population is required to prevent mutations and establish different variations, which can entirely evade immune scrutiny. COVID-19 vaccinations are harmless and can significantly decrease the number of deaths, critical case scenarios, cases showing significant symptoms, and the spread of infection due to COVID-19 globally . In respThe worldwide spread of numerous COVID-19 mutations calls into question whether current vaccines will give long-lasting protection. A vaccine generating responsive antibodies against receptor-binding protein comparable to naturally occurring infection implies that vaccines can, to some extent, lessen the degree of disease produced by natural conditions. Furthermore, mutations have little effect on T-cell responses to spikes, which means that variants can still induce serious illnesses. Again, as coronavirus transmutation continues to develop, the body’s immune response is continuously building its ability to deal with the mutant changes in the COVID-19 virus. After 6.2 months of successful immunization, memory B cells are constantly developing and are engaged in preventing reinfection. This information strongly impacts the fact that vaccinated people can respond swiftly and efficiently when exposed to the virus. It is revealed that various present messenger ribonucleic acid, adenovirus, and deactivated vaccine doses can elicit a noteworthy immunological response in contrast to SARS-CoV-2 receptor-binding domains in vaccine recipients. Individuals develop antibody responses against receptor-binding domains after 30 days of receiving both immunization doses. COVID-19 vaccines are safe like other vaccines, such as ribonucleic acid, adenovirus family, and deactivated vaccinations, and are similarly satisfactory compared to various vaccines, including the influenza vaccine .Because COVID-19 immunization rates have gone up worldwide, people wonder how prolonged this epidemic will exist. It is a question fraught with ambiguity. However, the assumption that sufficient people will ultimately develop antibodies to COVID-19 to preclude a major herd immunity threshold is becoming doubtful. Such a criterion is generally attained through elevated vaccination rates. Several researchers believed that once people began to get vaccinated in large numbers, population immunity would help society revert to normal. Several analysts predict the criterion at 60-70% of the community acquiring immunity from immunization or recent infection with the pathogen. However, while the epidemic approaches its second wave, perceptions are shifting. Youyang Gu, an autonomous data scientist, updated the title of his renowned COVID-19 forecasting model from “Path to Herd Immunity” to “Path to Normality” in February. He stated that attaining a population immunity threshold seems implausible owing to characteristics such as vaccine reluctance, the advent of novel variations, and the late advent of child vaccines .To achieve the aim of reducing and eliminating COVID-19, herd immunity must fulfill the requirements. The accomplishment of herd immunity is hardly possible unless any of the causes for the herd immunity concept is established . Three sDifferent assumptions made by researchers regarding herd immunityTo acquire population immunity to resist SARS-CoV-2, Anthony Fauci anticipated that it is essential to vaccinate 70-85% of the US population . PopulatBuilding herd immunity will reduce the probability of infection with COVID-19. In addition, it will significantly reduce the severity of reinfection and hospitalization. However, the duration to achieve herd immunity highly depends upon vaccination, completing the required dose, including booster doses, and controlling mutations. Worldwide continuous analysis of SARS-CoV-2 variants and their virulent impact will allow scientists to determine whether to update vaccines and other treatments. Newly emerging variants may diminish herd immunity, threaten unvaccinated people, and promote vaccination escape, predisposing people to severe illness or death. Most research has shown that immunizations are effective. Vaccine development for COVID-19 has advanced at an unprecedented rate in the last year, which was not previously conceivable. Achievement of herd immunity is a challenging idea to grasp. In global immunization, many countries are arranging vaccination campaigns, and vaccines have been administered exponentially.


Digital and mobile health interventions are increasingly being used to support healthy lifestyle change, including in certain high-risk populations such as those with severe mental illnesses (SMIs). Life expectancy in this population lags 15 years behind counterparts in the general population, primarily due to obesity-related health conditions.We tested the feasibility and usability of a 12-week interactive obesity treatment approach (iOTA) to adults with chronic SMIs  receiving treatment in community settings. The iOTA incorporates short message service (SMS) text messages to supplement monthly in-person health coaching.Factors hypothesized to be associated with weight change were illness severity and treatment engagement. Severe psychiatric symptoms were defined as baseline Clinical Global Impression severity score of >5. Criterion engagement was defined as a text messaging response rate >80% during the first 4 weeks of treatment. Disordered eating, assessed with the Loss of Control Over Eating Scores, was also evaluated. Participants provided qualitative data, further informing assessment of intervention feasibility, usability, and acceptability.F1,16=22.54, P<.001). Conversely, high symptom severity and lower text message response rates were associated with trend-level increases in weight . Loss-of-control eating was not observed to impact treatment outcome. Participants voiced preference for combination of live health coaching and text messaging, expressing desire for personalized message content.A total of 26 participants were enrolled. The mean age was 48.5 (SD 15.67) years; 40% (10/26) were Black and 60% (15/26) female. Participants with lower symptom severity and adequate engagement demonstrated significantly decreased weight (These results demonstrate the feasibility of delivering an adapted iOTA to SMI patients receiving care in community settings and suggest testable criteria for defining sufficient treatment engagement and psychiatric symptom severity, two factors known to impact weight loss outcomes. These important findings suggest specific adaptations may be needed for optimal treatment outcomes in individuals with SMI. The field of obesity medicine has embraced the concept that excess adiposity is a disease state with important neurobehavioral causes and consequences -3. Thus,Patients with chronic severe mental illness (SMI) are at high risk for developing obesity and related adverse health conditions, attributable to treatment with obesogenic medications , sedentaInteractive obesity treatment approaches (iOTAs) employing telephone or digital strategies have been used to engage lower-income and underrepresented communities in lifestyle changes that promote healthy body weight. For example, the Be Fit Be Well intervention, based on the well-known Dietary Approaches to Stop Hypertension program, produced weight loss at 24 months by extending health coaching with automated telephone messaging and internet-based self-guided content to increase engagement . Be Fit In this study, we tested the usability of the Working for You iOTA in settings where patients with SMIs are most likely to engage in psychosocial rehabilitation and mental health treatment—outpatient community clinical settings ,25. We sIndividuals ages 16 to 75 years who were actively engaged in outpatient community mental health clinic or clubhouse programming in the St. Louis and surrounding urban, suburban, and rural areas -46 were A priori study inclusion criteria were BMI >28 and diagnosis of a severe and persistent mental illness  confirmed with medical record review. Known eating disorder diagnosis, active substance use disorder, and acute suicidality were exclusionary.This study was approved by the Washington University in St. Louis institutional review board (protocol number 201706118). Capacity to provide informed consent was confirmed by assessing basic medical literacy using the Rapid Estimate of Adult Literacy in Medicine–Short Form (REALM-SF), a 7-item word recognition test, with a score of 5 or higher being consistent with an 8th grade reading level and minimal ability to understand medical terminology  and the The parent iOTA was developed for low-wage hospital workers participating in the Working for You study . BehavioIn the Working for You study, participants met one-to-one with a health coach on a quarterly basis. At the first study visit, the health coach met with participants to obtain written informed consent, review the individual’s health risk assessment, and choose up to 3 behavior change goals related to principles of energy balance. Goals were set based on behaviors identified as those (1) in highest need of change, (2) for which the participant has high self-efficacy and readiness for change, (3) for which the participant identifies few change barriers, and (4) that fulfill the intended impact on energy balance. Goals domains are based on simple, concrete behavior changes known to be effective based on empirical evidence of link to energy balance/weight and relevance to low-income populations ,41. SubsParticipants in this study underwent 12 weeks of treatment consisting of either monthly one-on-one in-person visits for participants seen in the outpatient clinic setting or monthly group sessions to deliver educational content, directly followed by brief one-to-one goal-setting for participants seen in the clubhouse setting. To more closely parallel the chronic care model in which most SMI patients receive care, participants in this study met monthly with health coaches. Additional treatment adaptations included adding weekly phone check-ins as needed, elements of problem-solving therapy   and motiAs in the parent intervention, participants were prompted weekly to respond via SMS text with their weight and progress toward health goals. During monthly in-person coaching meetings, the health coach reviewed progress toward goals, problem solved barriers to goal achievement, and assisted participants in selecting new goals, if necessary, at each monthly meeting based on mastery, preference, and energy balance priority. Session 1 consisted of a weigh-in and discussion of the relationship between health behaviors, health goals, and body weight (10 minutes), followed by discussion of energy balance and self-monitoring (30 minutes). The session concluded with a review of health goals, revising and scaling difficulty as appropriate (10 minutes). Subsequent visits followed the same format, with the 30-minute discussion including session-specific content . The order of the content delivered in the sessions was determined based on prior behavioral weight loss treatment development experience in youth and adults with SMI treated in community settings, where qualitative efforts identified the greatest health behavior knowledge and skill deficits in this population were understanding nutrition and healthy meal planning ,53.The primary objective of this study was to evaluate factors associated with engagement, a primary indicator of successful weight loss in behavioral lifestyle interventions ,54. We ed=0.82, P<.001), strong content validity and internal consistency, factor structure, and convergent and discriminant validity [The presence of loss-of-control eating was assessed with the 7-item Loss of Control Over Eating Score (LOCES) , which hvalidity . The assWe evaluated participant experiences with the in-person and text-messaging aspects of the intervention, specifically assessing satisfaction with treatment content, visit and text messaging frequency, and usability of the text messaging portion of the intervention. At the end of the 12-week study, participants completed a 5-question treatment satisfaction survey. Questions were based on the Contextual Technology Adaptation Process (CTAP) developed by Lyon and colleagues .The CTAP model is based on user-centered design and implementation science principles and incorporates mixed quantitative and qualitative assessments considering aspects of the technology under study , contexts in which the technology will be used , and resources available for adaptation efforts . CTAP involves 5 phases, including initial assessment in relevant contexts, testing of unadapted technology, adaptation, retesting, and sustained iterative assessment and adaptation processes.This study used early-phase CTAP approaches to assess the acceptability of the unadapted technology in a new user population (adults with SMI) and treatment settings . Our CTAP questionnaire consisted of 5 questions focused on satisfaction and acceptability of the (1) overall program, (2) in-person health coaching visits, (3) goal options, (4) text message responses, and (5) health tip text message content. Response options were 1=very unsatisfied or unhelpful to 5=very satisfied or helpful. Each domain included 3 corresponding open-ended questions: What did you like? What did you dislike? What would you change?P<.05 using a 2-tailed test. CTAP responses were tabulated and presented as frequency and percentage followed by a representative quotation from corresponding open-ended questions.Repeated measures analysis of covariance was used to test for the effect of time on weight change, including 2-level factors for membership in included/excluded participant group , and treatment setting, as well as an exploratory covariate representing score on the LOCES. Finally, we evaluated whether treatment setting for monthly in-person (one-to-one versus group) sessions influenced weight change over time. Significance was set at A total of 26 participants were recruited for the study . The mean age of the overall population was 48.5 (SD 15.67) years; 60% (15/26) were white and 62% (16/26) female . One parOf the 26 participants who enrolled, 13 received in-person health coaching in a group-based clubhouse setting  and 12 received one-to-one health coaching with a study interventionist . One participant lost eligibility due to relapse in substance use. In the pooled treatment group, mean weight change was –0.7 (SD 15.4) lbs . Eight participants met the exclusion criteria under evaluation; 2 participants had a Clinical Global Impression score >5; mean weight change during treatment in this group was 32.9 (SD 25.1) lbs. Six participants had a text message response rate <80%; mean weight change in this group was 8.1 (SD 3.8) lbs.F1,23=17.98, P<.001), explained by lower symptom severity and >80% text-messaging response rate in the first 4 weeks of participation (n=18) exhibiting a significant decrease in weight . Participants with high symptom severity and low treatment engagement (n=8) had a trend-level increase in weight .Using repeated measures analysis of covariance , a signiF1,23=2.22, P=.15) or LOCES score .We also tested the interactive effect of time and treatment setting, and LOCES score on change in weight over 12 weeks of iOTA. No significant interactions were observed with treatment setting  in that they provided an easy option for accountability and self-monitoring. However, to be associated with the selected health coals, responses included prescribed tags consisting of 3-5 letters in all caps  were difficult to remember; omitting the response tag or responding with an incorrect tag generated error messages that may have resulted in abandonment of the check-in process. Finally, participants in general felt the text message content was helpful but expressed a desire for customizable text messages relevant to personalized goals.In this study, we explored the feasibility of delivering an interactive text messaging weight loss intervention to adults with SMIs treated in community clinical settings. Our initial hypothesis, driven by results from previous studies of weight loss interventions in SMI populations ,59, was In this usability test, engagement, measured by percentage response to SMS messages within the first month of participation, and lower severity of illness at baseline predicted change in weight at 12 weeks. Qualitative data on user experience and user satisfaction indicated that participants felt positively toward text messaging. Participants still felt that in-person visits were important but would also be acceptable if done remotely via telehealth or text. Like prior studies testing usability of health behavior change apps , particiIt is well known that obesity and mental illness are highly comorbid, with most patients seeking obesity treatment having two or more treatable diagnoses ,12. FurtThis study is subject to important limitations; namely, the sample size is small and relatively heterogeneous in terms of diagnosis, care setting, and baseline weight and age. Thus, adequate power to detect between-group differences in subgroup analyses is limited. It should also be noted that the inclusion of patients engaged in services only limits the generalizability of the results; people with SMI are often disengaged from clinical care for a variety of reasons having to do with disparity and disadvantage . As a reThese data are relevant to future study design considerations and support further testing of specific exclusion criteria for defining treatment engagement and psychiatric symptom control. Future studies applying these selection criteria may be important in evaluating the effect of this iOTA in SMI but will need to consider methods for reaching individuals who may benefit most from mHealth interventions—those who are disengaged from care, from underrepresented or disadvantaged populations, or who live in rural areas. Finally, more comprehensive symptom assessments may be needed to understand the effect of eating disorder symptoms on weight change outcomes in this populations. Nonetheless, these results demonstrate the feasibility of delivering an adapted iOTA intervention to SMI patients receiving care in clubhouse and community mental health clinic settings and suggest testable criteria for defining sufficient treatment engagement and psychiatric symptom severity.


In total, 2761 CpGs located on 160 centrosome genes for 6 cancers were included in the analysis. Cancer-specific models demonstrated a high accuracy in terms of the area under the receiver operating characteristic (ROC) curve (AUC > 0.9) in five cancers and showed tissue specificity. This study enhanced our understanding of the epigenetic mechanisms underlying the DNA methylation of centrosome-related genes in cancers, and showed the potential of these epigenetic modifications as novel cancer biomarkers.The centrosome plays a central role for cellular signaling and is critical for several fundamental cellular processes in human cells. Centrosome abnormalities have been linked to multiple solid tumors and hematological malignancies. We sought to explore the potential role of the DNA methylation, a critical epigenetic modification, of centrosome-related genes in different cancers. The 450K array DNA methylation data and RNA-seq data were downloaded for ~4000 tumor samples and ~500 normal controls from The Cancer Genome Atlas (TCGA) project, covering 11 major cancer types. Cancers with more than 30 normal controls were retained for analysis. Differentially modified CpGs of centrosome genes were identified, and cancer-specific epigenetic models were developed using a machine-learning algorithm for each cancer type. The association between the methylation level of differential CpGs and the corresponding gene expression, as well as the co-localization of the differential CpGs and  The centrosome is a non-membranous organelle comprised of centrioles surrounded by pericentriolar material (PCM) ,2,3 and Specifically, centrosome abnormalities have been implicated in solid tumors such as lung, breast, prostate, colon, ovarian and pancreatic cancer ,12,13,14In the current study, we systematically analyzed the DNA methylation data from The Cancer Genome Atlas (TCGA) Project , specifiThe Support Vector Machine (SVM)  was usedTo determine whether tissue specificity caused cancer-specific CpGs, a principal component analysis (PCA) was carried out for the CpGs in normal samples. When plotting the 1st principal component against the 2nd component, a tissue-specific pattern was observed , indicatt-test, p-value < 0.05; The Pearson’s correlation between the methylation level of each CpG site and its local host gene was calculated for each type of cancer in all samples, then separately for tumor and normal samples . In all 2 fold-change was calculated as the observed overlapping counts divided by the mean of the null distribution. The most significant enrichment was found in H3K9me1 for BRCA, HNSC, LUAD, and UCEC  from 5-Hydroxymethylcytosine (5hmC), which could have different biological implications. Future studies using TAB-array or 5hmC-specific approaches could help address this issue ,31. FinaIn total, ~4000 tumor samples and ~500 normal controls that covered 11 major cancer types from TCGA were analyzed in the current study , includihttps://portal.gdc.cancer.gov/; accessed on 11 November 2021). The centrosome-related gene list was based on Jakobsen et al. [2 ratio of the intensities of methylated probes versus unmethylated probes [Publicly available TCGA DNA methylation was downloaded and aggregated at the GDC Legacy Archive  con et al. ; (iii) hd probes , was sumTCGAbiolinks R package [The publicly available RNA-seq data was obtained from GDC using the  package . Only thlimma R package [To detect differentially modified CpGs between tumor and normal in each cancer type, the  package  was used package . A resule1071 was used in the model training [The support vector machine (SVM) is a binary classification algorithm . The maitraining . Both liThe SVM classifier with the Gaussian kernel is formulated as follows:2 fold change >1 and p-value < 0.0005 were used as features. If these criteria were not met, the top 5 CpGs with the smallest p-values were used. A five-fold cross validation was used during the training process to get the best performance. After the model was trained, the remaining 20% of the samples were used to test the model performance, and the area under the receiver operating characteristic (ROC) curve (AUC) was calculated. The model for each cancer was also tested in other cancer data, in order to prove cancer specificity.In order to avoid an over-fitting problem for model training in this section, 80% of randomly selected samples were used for training purposes. Cancer-specific CpGs with logTo detect the association between the methylation levels of cancer-specific CpGs and gene expression phenotypes, correlations between the methylation levels and corresponding 139 gene expressions in tumor samples were evaluated. A linear model was fitted for each CpG with its corresponding gene for each cancer type separately: i.e., 2 fold-change was calculated as:We obtained uniformly processed narrow peaks for transcription factor binding sites and broad peaks for histone markers from the ENCODE (Encyclopedia of DNA Elements) Project . Peaks fIn conclusion, by utilizing the TCGA data, this work explored the distinct role of cytosine modifications for centrosome-related genes and revealed the cancer-specific cytosine modification patterns. Furthermore, this cancer-specific pattern of epigenetic modification demonstrated its potential as a novel cancer biomarker that may aid in diagnosis and targeted screenings for at-risk individuals.


The pandemic caused by severe acute respiratory coronavirus virus 2 (SARS-CoV-2) has dramatically increased cheshospitalizations, and it is often difficult to determine whether there is a bacterial or fungal coinfection at time of presentation. In this study, we sought to determine the rates of coinfection and utilization of antibiotics in SARS-CoV-2 disease.Retrospective chart review of patients hospitalized with COVID-19 pneumonia from April 13, 2020, to July 14, 2020.P = .01) and to have leukocytosis  and were less likely to have a procalcitonin level <0.25 ng/mL . In total, 45 patients had positive blood cultures collected during hospitalization, 16 of which were clinically significant. Of the clinically significant blood cultures, 5 were collected <48 hours of admission. Moreover, 18 sputum cultures were clinically significant, 2 of which were collected within 48 hours of admission.In total, 277 patients were hospitalized for COVID-19 pneumonia during this period. Patients that received antibiotics within 48 hours of presentation were more likely to be febrile (59.3% vs 41.2%; Bacterial and fungal coinfections in COVID-19 appear to be rare on presentation; thus, this factor may be a good target for enhanced antibiotic stewardship. Many of these patients present with signs and symptoms that are the same as that of bacterial pneumonia, prompting empiric antibiotic usage. The current Infectious Diseases Society of America/American Thoracic Society guidelines recommend empiric antimicrobial therapy in patients with influenza infection and radiographic evidence of community-acquired pneumonia in both the inpatient and outpatient setting. However, data on the clinical circumstance on antibiotic utilization in COVID-19 remain sparse. A review of the literature found that 5%–27% of COVID-19 cases had an associated secondary infection, and a Virginia study noted a significant increase in ceftriaxone and azithromycin use in the medical intensive care unit (ICU) during the pandemic. In this study, we sought to capture the antibiotic utilization and rate of secondary infection in patients with COVID-19.Since the start of the pandemic, coronavirus disease 2019 (COVID-19) has infected millions of patients and has caused significant mortality worldwide.International Classification of Diseases, Tenth Revision (ICD-10) codes. Laboratory values were recorded as the first values available on presentation. Pneumonia was defined by chart review based on clinical characteristics of patients at presentation. Only commonly pathogenic organisms were considered clinically significant, and organisms that are typically considered as a contaminant or a colonizer  were not considered clinically significant. Pathogenic coagulase-negative Staphylococcus in the blood was defined as patients having received targeted therapy or deemed to be clinically significant based on documentation. These clinical parameters were compared between patients who received empiric antibiotics within 48 hours of admission and those who did not.This study was a retrospective chart review of all adult patients with positive nasopharyngeal SARS-CoV-2 polymerase chain reaction (PCR) assay admitted to Olive View–University of California–Los Angeles Medical Center, a hospital funded by Los Angeles County in California. Only patients suspected of having COVID-19 pneumonia as documented in the medical records were included, and asymptomatic patients who were admitted for an unrelated cause who screened positive with the SARS-CoV-2 PCR were excluded. Information regarding patient demographics, clinical findings at presentation and during hospitalization, laboratory results, and microbiology were collected and managed in Microsoft Excel software . Comorbidities were defined based on clinical documentation and Antibiotic utilization was further characterized in detail. Antibiotic delivery was stratified as having started either early (within 48 hours of admission) or late (after 48 hours). The class, specific antibiotics, and days of therapy were abstracted by manual chart review.2 or Fisher exact test. Continuous variables were evaluated using the Student t test or the Mann-Whitney U test where appropriate.Categorical variables were analyzed using the χP = .01) and were less likely to have leukocytosis , neutrophilia , or lymphopenia . They were more likely to have chest radiograph findings that were negative for any acute processes . In terms of inflammatory markers, individuals who were not administered antibiotics within 48 hours of hospitalization had lower mean levels of D-dimer , ferritin , and C-reactive protein ; they were also more likely to have a procalcitonin level <0.25 ng/mL . We detected no statistically significant differences in symptoms between the 2 groups. Patients who were not administered antibiotics were less likely to require supplemental oxygen  or intubation  during the admission. They also had a lower in-hospital mortality rate .Overall, 684 patients with a positive SARS-CoV-2 nasopharyngeal PCR between April 13, 2020, to July 14, 2020, were included. Of these, 277 had been admitted for COVID-19 pneumonia and either died during their hospitalization or were discharged. Also, 51 patients did not receive antibiotics within 48 hours of hospitalization and 226 patients did . For patients with positive sputum cultures  patients had positive blood cultures during their hospitalization  antibiotics were prescribed in 13.8% and 11.6% of patients who had antibiotics initiated within 48 hours of admission, respectively, with median durations of 2 days and 1 day, respectively. When an antibiotic was initiated after 48 hours, the most commonly used was vancomycin, followed by cefepime, with median durations of 3 and 5.5 days, respectively . Anti-pseudomonal and anti–methicillin-resistant  the circumstances in which they are used have not been well studied. A published study in Michigan analyzed 1,705 patients with COVID-19 and aimed to describe the number of bacterial coinfections. In that study, 56.6% of patients were prescribed early antibiotic therapy, and only 3.5% of patients had confirmed community-onset bacterial infections. Our study showed similar rates of antibiotic use despite low rates of culture confirmed bacterial coinfections. It appears that patients with clinically significant cultures (either sputum or blood) tended to have cultures collected several days into their hospitalization in our study, suggesting nosocomial acquisition.The current pandemic is unprecedented, with high mortality. Although prescriber utilization of broad-spectrum antibiotics has been documented in the literature,; however, these studies do not have patient-level data on the duration and timing with which each antibiotic was prescribed. Not surprisingly, in our study therapeutics targeting community-acquired pathogens  were the antibiotics most commonly prescribed within 48 hours of admission. Broad-spectrum agents were still used during this period; however, they were generally de-escalated quickly with a median duration of ˜1 day. At our institution, broad-spectrum agents have prespecified indications. All antibiotic use, however, is reviewed by our antibiotic stewardship team, who then help in the de-escalation of therapy. Our data also suggest that most broad-spectrum antibiotic use occurred later in the hospitalization rather than as empiric therapy on admission.Previous studies have noted an increase in antibiotic utilization in both “narrow-” and “broad-spectrum” categories and the World Health Organization has recommended empiric antibiotic therapy for severe COVID-19. Our results indicate that patients were more likely to get antibiotics in the presence of certain clinical parameters such as fevers or leukocytosis; however, these signs are nonspecific and are not specifically characteristic of a bacterial infection.One explanation of the use of empiric antibiotics in patients is the difficulty in distinguishing between a bacterial process and COVID-19. Recent guidelines have suggested empiric antibiotics for patients with suspected but unconfirmed COVID-19,Our study had several limitations. It was a single-center retrospective study, so our findings may not be generalizable to all hospitals. Not all patients had blood and/or sputum cultures drawn during the hospitalization, making it hard to distinguish the true secondary infection rate. Also, a pneumonia multiplex PCR film array panel was not routinely used for community-acquired pneumonia at our hospital, so we may have underestimated the true incidence of bacterial coinfection. This diagnostic test would have a higher sensitivity in identifying bacteria than routine cultures would. Lastly, rates of antibiotic use may have been overestimated because azithromycin, which was used as a COVID-19–specific therapy early in the pandemic, was included in our analysis as an antibiotic therapy. COVID-19 presenting similarly to a bacterial process has certainly not aided in efforts to curb antibiotic use. In our study, the rate of concurrent bacterial processes in COVID-19, as defined by culture-positivity, was very low but antibiotic use was widespread. The pandemic therefore raises a unique stewardship opportunity, and future studies are needed to better characterize the utility of antibiotics in the management of patients with COVID-19, so that its unnecessary antibiotic use can be minimized.Antimicrobial resistance continues to be a global crisis.


Cancer-of-unknown-primary-origin (CUP) is challenging to diagnose and treat, and little is known about its diagnostic work-up, treatment, and outcomes in routine healthcare. We examined data from elderly patients (at least 66 years old) diagnosed with CUP in real-world US clinical practice, using the Surveillance, Epidemiology, and End Results–Medicare-linked database. Only half of elderly patients with CUP received all three diagnostic work-up procedures , as recommended by guidelines. Patients who received all three diagnostic work-up procedures were more likely to receive any type of anticancer treatment, and patients who did not receive full diagnostic work-up had shorter median overall survival, particularly with increasing age. Overall, these results suggest that further studies are needed to understand why many patients given a diagnosis of CUP do not receive complete diagnostic work-up or treatment. Further research into improving diagnostic work-up and treatment effectiveness in patients diagnosed with CUP is required.Knowledge of contemporary patterns of cancer-of-unknown-primary-origin (CUP) diagnostic work-up, treatment, and outcomes in routine healthcare is limited. Thus, we examined data from elderly patients diagnosed with CUP in real-world US clinical practice. From the Surveillance, Epidemiology, and End Results–Medicare-linked database, we included patients ≥ 66 years old with CUP diagnosed between 1 January 2013 and 31 December 2015. We analyzed baseline demographics, clinical characteristics, methods of diagnostic work-up , treatment-related factors, and survival. CUP diagnosis was histologically confirmed in 2813/4562 patients (61.7%). Overall, 621/4562 (13.6%) patients received anticancer pharmacotherapy; among these, 97.3% had a histologically confirmed tumor and 83.1% received all three procedures. Among those with a histologically confirmed tumor, increasing age, increasing comorbidity score, not receiving all three diagnostic measures, and having a not-further specified histologic finding of only ‘malignant neoplasm’ were all negatively associated with receipt of anticancer pharmacotherapy. Median overall survival was 1.2 months for all patients. Median time between CUP diagnosis and treatment initiation was 41 days. Limited diagnostic work-up was common and most patients did not receive anticancer pharmacotherapy. The poor outcomes highlight a substantial unmet need for further research into improving diagnostic work-up and treatment effectiveness in CUP. Cancer-of-unknown-primary-origin (CUP) describes a heterogeneous group of metastatic cancers, without an identifiable primary tumor despite thorough clinical work-up . AlthougInternational clinical practice guidelines   and, conThis study comprised population-based US cancer registry data from the SEER Program with linked Medicare claims of billed healthcare services. Patients were included if a CUP diagnosis  was registered as their first malignancy at age ≥ 66 years between 1 January 2013 and 31 December 2015, according to coding criteria in the SEERM database  comorbidity score . The datThe NCI comorbidity score is used to predict non-cancer-related deaths in patients with cancer via SEERM data. It includes disease conditions determined from inpatient and physician claims for a 365-day period prior to the month of diagnosis .We assessed the use of diagnostic work-up between 52 weeks prior to CUP diagnosis and up to 30 days thereafter, or up to the start of treatment if that occurred earlier. Based on ESMO and NCCN guidelines , a baselP values. To further examine the role of diagnostic work-up in the receipt of pharmacotherapy, multivariate logistic regression was used to adjust for differences in baseline demographics  and clinical characteristics  between patients who received anticancer pharmacotherapy and those who did not. Further information regarding the compilation of study-related code lists is provided in the For treatment-related factors, use of anticancer pharmacotherapy, as well as cancer surgery and radiotherapy, time to treatment initiation, and number of days where treatment was received  were described over the complete follow-up period. Median and percentage survival at 1, 2, 6, 12, 24, 36, and 60 months after diagnosis, using Kaplan–Meier estimates stratified by age groups  and according to receipt of anticancer pharmacotherapy, were calculated with comparisons conducted using log-rank tests to produce Overall, 6116 patients aged ≥66 years old had a first diagnosis of CUP between 1 January 2013 and 31 December 2015, of which 4562 (74.6%) patients were eligible . Among tMedian age at first CUP diagnosis was 80 years  had an NCI comorbidity score of zero, whereas low-, middle-, and high-level scores were each recorded for ~20–25% of patients . A comorAs indicated by the volume of claims for biopsies, immunohistochemistry, and imaging , diagnosOf the 4562 patients in the study, only 621 (13.6%) received any anticancer pharmacotherapy . Among tOver the entire course of treatment, the majority of patients treated with pharmacotherapy received chemotherapy only (369/621 [59.4%]), while 22 (3.5%) received cancer immunotherapy . Targetep < 0.0001) for treated and untreated patients, respectively. The highest 3-year survival (50.5% [n = 34]) was observed for patients who were treated with surgery and radiotherapy only (n = 1679]) was seen among patients who did not receive histologic confirmation of their tumor and were not treated  diagnosed with CUP in real-world clinical practice.Only half of elderly patients with CUP received all three diagnostic work-up procedures  as recommended by the ESMO/NCCN guidelines ,16. Our While studying CUP using cancer registry-based ,25 as weIn our study, patients with complete baseline diagnostic work-up were more likely to receive any type of anticancer treatment, suggesting that a complete diagnostic work-up was mostly regarded as mandatory before initiating therapy. In particular, the best survival outcomes were seen in those patients determined to belong to a subset with good prognosis, such as those with a single site of disease who may be treated with surgery and/or radiotherapy. Conversely, omitting diagnostic tests in unfit patients who appear to have advanced and widely metastatic disease is justifiable and may reflect rapid clinical deterioration that prompts the treating physician to limit diagnostic procedures early. This may also explain why oncologists made no attempt to clarify the unspecified histology of ‘malignant neoplasm’ in untreated patients. However, we cannot rule out that treating doctors do not recommend completion of diagnostic investigations because of pessimism, lack of timely access to diagnostic investigations, or lack of knowledge regarding available treatment options. The likelihood of receiving anticancer pharmacotherapy increased with younger age, reduced comorbidity score, having a histology of squamous, neuroendocrine, or small-cell carcinomas, and other more specific histologies (compared with adenocarcinoma). Although there were no notable disparities among patients who received histologic confirmation based on race or urban/rural settings, histologic confirmation was slightly less common among those with a higher poverty index. A higher poverty index was also found to be negatively associated with receipt of anticancer pharmacotherapy. Further research is required to better understand referral pathways to receive more complete diagnostic work-up and treatment among patients with CUP.Patients who did not receive a full diagnostic work-up had shorter median overall survival, particularly with increasing age. The high early and overall mortality among patients who did not receive histologic confirmation suggests that these patients in general were nevertheless suffering from cancer; although without histologic confirmation, some of these individuals may have had more easily treatable cancers than CUP, another treatable diagnosis mimicking cancer on imaging, or a relapse of a pre-existing malignancy that might have been missed ,30,31. GThe strengths of this study include the use of population-based representative data for patients with CUP aged ≥ 66 years old and broad examination of claims-based diagnostic activities. Limitations include: (1) lack of younger patients ; (2) soThis SEERM study suggests that further research is needed to understand why many patients given a diagnosis of CUP do not receive a complete diagnostic work-up or treatment. A substantial unmet need exists for timely access to more accurate and rapid diagnostic work-ups, as well as more effective treatments for patients diagnosed with CUP. Baseline diagnostic work-up was performed on patients who subsequently received anticancer pharmacotherapy, and significantly better survival outcomes were seen in patients who were well enough and able to access guideline-recommended diagnostic work-up. However, poor general health status of patients or aggressive, advanced disease may lead the treating physician to cease diagnostic procedures prior to establishing a diagnosis. Furthermore, among those who received treatment, ~45% received up to 4 days of treatment only, implying that lack of response or poor tolerance of existing therapies is common and that more specific treatment options are rarely available. High-resolution clinical studies on CUP are needed to provide further insights into the unmet needs observed in this study.