Clinicopathological and prognostic features of subungual melanoma in situ / 中华病理学杂志

Objective: To investigate the clinicopathological characteristics, immunohistochemical profiles, molecular features, and prognosis of subungual melanoma in situ (SMIS). Methods: Thirty cases of SMIS were collected in Fudan University Shanghai Cancer Center, Shanghai, China from 2018 to 2022. The clinicopathological characteristics and follow-up data were retrospectively analyzed. Histopathologic evaluation and immunohistochemical studies were carried out. By using Vysis melanoma fluorescence in situ hybridization (FISH) probe kit, combined with 9p21(CDKN2A) and 8q24(MYC) assays were performed. Results: There were 8 males and 22 females. The patients' ages ranged from 22 to 65 years (median 48 years). All patients presented with longitudinal melanonychia involving a single digit. Thumb was the most commonly affected digit (16/30, 53.3%). 56.7% (17/30) of the cases presented with Hutchinson's sign. Microscopically, melanocytes proliferated along the dermo-epithelial junction. Hyperchromatism and nuclear pleomorphism were two of the most common histological features. The melanocyte count ranged from 30 to 185. Most cases showed small to medium nuclear enlargement (29/30, 96.7%). Pagetoid spread was seen in all cases. Intra-epithelial mitoses were identified in 56.7% (17/30) of the cases. Involvement of nailfold was found in 19 cases, 4 of which were accompanied by cutaneous adnexal extension. The positive rates of SOX10, PNL2, Melan A, HMB45, S-100, and PRAME were 100.0%, 100.0%, 96.0%, 95.0%, 76.9%, and 83.3%, respectively. FISH analysis was positive in 6/9 of the cases. Follow-up data were available in 28 patients, and all of them were alive without disease. Conclusions: SMIS mainly shows small to medium-sized cells. High melanocyte count, hyperchromatism, nuclear pleomorphism, Pagetoid spreading, intra-epithelial mitosis, nailfold involvement, and cutaneous adnexal extension are important diagnostic hallmarks. Immunohistochemistry including SOX10 and PRAME, combined with FISH analysis, is valuable for the diagnosis of SMIS.

Plurihormonal PIT1-lineage pituitary neuroendocrine tumors: a clinicopathological study / 中华病理学杂志

Objective: To investigate the clinicopathological characteristics of plurihormonal PIT1-lineage pituitary neuroendocrine tumors. Methods: Forty-eight plurihormonal PIT1-lineage tumors were collected between January 2018 and April 2022 from the pathological database of Sanbo Brain Hospital, Capital Medical University. The related clinical and imaging data were retrieved. H&E, immunohistochemical and special stains were performed. Results: Out of the 48 plurihormonal PIT1-lineage tumors included, 13 cases were mature PIT1-lineage tumors and 35 cases were immature PIT1-lineage tumors. There were some obvious clinicopathological differences between the two groups. Clinically, the mature plurihormonal PIT1-lineage tumor mostly had endocrine symptoms due to increased hormone production, while a small number of immature PIT1-lineage tumors had endocrine symptoms accompanied by low-level increased serum pituitary hormone; patients with the immature PIT1-lineage tumors were younger than the mature PIT1-lineage tumors; the immature PIT1-lineage tumors were larger in size and more likely invasive in imaging. Histopathologically, the mature PIT1-lineage tumors were composed of large eosinophilic cells with high proportion of growth hormone expression, while the immature PIT1-lineage tumors consisted of chromophobe cells with a relatively higher expression of prolactin; the mature PIT1-lineage tumors had consistently diffuse cytoplasmic positive staining for keratin, while the immature PIT1-lineage tumors had various expression for keratin; the immature PIT1-lineage tumors showed more mitotic figures and higher Ki-67 proliferation index; in addition, 25.0% (12/48) of PIT1-positive plurihormonal tumors showed abnormal positive staining for gonadotropin hormones. There was no significant difference in the progression-free survival between the two groups (P=0.648) by Kaplan-Meier analysis. Conclusions: Plurihormonal PIT1-lineage tumor belongs to a rare type of PIT1-lineage pituitary neuroendocrine tumors, most of which are of immature lineage. Clinically increased symptoms owing to pituitary hormone secretion, histopathologically increased number of eosinophilic tumor cells with high proportion of growth hormone expression, diffusely cytoplasmic keratin staining and low proliferative activity can help differentiate the mature plurihormonal PIT1-lineage tumors from the immature PIT1-lineage tumors. The immature PIT1-lineage tumors have more complicated clinicopathological characteristics.

Structural equation model analysis of infectious disease-specific health literacy scale in China / 中华流行病学杂志

Objective: To explore the relationship between different dimensions of infectious disease-specific health literacy scale in China. Methods: Structural equation model (SEM) was employed to assess the psychometric properties of the infectious disease-specific health literacy scale. Based on the database from a randomly selected sample of 4 499 adult residents in three provinces in China, from March to May 2015. AMOS 21.0 software was used to build the SEM for data analyses. Results: SEM analyses showed a good model fit of data, with the following satisfied parameters: goodness-of-fit index was 0.969, adjusted goodness-of-fit index was 0.962, root mean square residual was 0.038, root mean square error of approximation was 0.038, standardized root mean square residual was 0.032, Tacker-Lewis index/non-normed fit index was 0.926, comparative fit index was 0.934, normed fit index was 0.925, relative fit index was 0.915, incremental fit index was 0.934, parsimony goodness-of-fit index was 0.782, parsimony-adjusted normed fit index was 0.817, parsimony-adjusted comparative fit index was 0.825 and critical N was 702. The established SEM showed that the total influence path coefficient of "infectious disease-related knowledge and values" on the "infectious disease prevention" , "management or treatment of infectious diseases" and "identification of infection sources" were 0.771, 0.744 and 0.843, respectively. The total influence path coefficients of "identification of infection sources" , "infectious disease prevention" on "management or treatment of infectious diseases" were 0.164 and 0.535, respectively. The effect of "infectious disease-related knowledge and values" on "management or treatment of infectious diseases" appeared the greatest (55.4%), followed by "infectious disease prevention" (28.6%) and "identification of infection sources" (2.7%). Conclusion: This SEM could be optimistically used for planning and evaluation of health education and promotion programs on infectious diseases prevention.

Risk of bias assessment: (8) Risk of Bias in Systematic Review (ROBIS) / 中华流行病学杂志

This paper introduces the Risk of Bias in Systematic Review (ROBIS), including: 1) the development of ROBIS, 2) three phases of ROBIS tool judging the overall risk of bias that related to systematic reviews, and 3) illustration on the application of ROBIS in a published systematic review. ROBIS is the first rigorously developed tool which is specifically designed to assess the risk of bias in systematic reviews. ROBIS will help improve the process of risk assessment on bias which appeared in overviews and guidelines.

Analysis on the current situation of insufficient sleep and its association with physical exercise among Chinese Han students aged 9-18 years, in 2014 / 中华流行病学杂志

Objective: To describe the situation of insufficient sleep and the association between insufficient sleep and physical exercise, among Chinese Han students aged 9-18 years. Methods: We selected 172 197 Chinese Han students aged 9-18 years from the project 2014 Chinese National Survey on Students Constitution and Health. The average sleep duration per day of less than 9 h for children aged 9-12 years and of less than 8 h for adolescents aged 13-18 years, were defined as insufficient sleep. We described the distribution of sleep duration and the prevalence rates of insufficient sleep for each subgroup. Logistic regression models were established to assess the association between insufficient sleep and physical exercise. Results: In 2014, 6.6%, 30.8%, 26.3%, 20.8%, 13.8% and 1.8% of the Chinese Han students self-reported sleep duration were <6, 6-, 7-, 8- and ≥10 h, respectively. The overall prevalence rate of insufficient sleep was 77.2%, with 75.8% for boys and 78.6% for girls. No gender disparity was found at each 9-11 age groups. However, in the 12-18 age groups, the prevalence rates for girls were significantly higher than that for boys. The prevalence rates of insufficient sleep for primary school, middle school and high school students were66.6%, 74.1% and 93.8%, respectively. Rates were increasing with age for children aged 9-12 years and adolescents aged 13-18 years respectively. The three provinces with the lowest prevalence rates of insufficient sleep were Zhejiang (68.8%), Jiangsu (66.7%) and Shaanxi (65.2%). Data from the logistic regression models revealed that, when comparing to those students with only exercise of <0.5 h per day, the exercise hours of 0.5-1 h (OR=0.72, 95%CI: 0.69-0.74) or ≥1 h (OR=0.46, 95%CI: 0.44-0.47) per day seemed as protective factors for insufficient sleep. When compared with physical exercise frequency <2 times per week, the 2 times (OR=0.82, 95%CI: 0.78-0.86) or >2 times (OR=0.65, 95%CI: 0.62-0.68) frequencies also appeared as protective. Conclusions: The prevalence rate of insufficient sleep prevailing among students aged 9-18 years was high, in China. Our data called for setting up effective measures to deal with this situation.

Epidemiological features of hepatitis C and its related influencing factors in Shandong province, 2007-2016 / 中华流行病学杂志

Objective: To analyze the epidemiological characteristics, dynamic trend of development and related influencing factors of hepatitis C in Shandong, China, 2007-2016, also to provide epidemiological evidence for prevention and control of HCV. Methods: National surveillance data of hepatitis C from 2007 to 2016 in Shandong was used, with distribution and clustering map of hepatitis C drawn at the county level. Panel Poisson regression was used to explore the influencing factors of hepatitis C at the city level. Results: The incidence of hepatitis C in Shandong increased from 1.49/100 000 in 2007 to 4.72/100 000 in 2016, with the high incidence mainly clustered in the urban regions in Jinan, Zibo, Weihai et al. and surrounding vicinities. Majority of the cases were young adults, with 53.16% (14 711/27 671) of them being farmers. Results from the Multiple panel Poisson regression analysis indicated that factors as: population density (aIRR=1.07, 95%CI: 1.05-1.10), number of hospital per hundred thousand people shared (aIRR=1.16, 95%CI: 1.08-1.24), expenditure of medical fee in rural (aIRR=1.21, 95%CI: 1.08-1.37) and the proportion of the tertiary industry (aIRR=1.08, 95%CI: 1.07-1.09) were all correlated to the incidence of hepatitis C. Conclusions: The incidence of hepatitis C had been increasing rapidly in recent years, in Shandong. Prevention and control of HCV should focus on high risk population. In addition, rural, especially in areas with lower economics provision should be under more attentions, so as to find more concealed cases for early treatment.

Prospective association between childhood abuse experiences and depressive symptoms in adolescence / 中华流行病学杂志

Objective: To evaluate the prospective association between childhood abuse experiences and depressive symptoms in adolescence. Methods: Students in grade 3 and 4 from three primary schools were selected, with informed consent, through convenience cluster sampling in Bengbu, Anhui province in May 2013. The students' body height, weight were assessed. Childhood abuse experiences including emotional, physical or sexual abuses, as well as depressive symptoms were reported by children themselves. Data on parental educational background and household economic status were collected through parent questionnaire. A follow up was conducted 4 years later after baseline survey. Depressive symptoms were evaluated by using Children's Depression Inventory at baseline survey, and by using Mood and Feeling Questionnaire at follow-up. Logistic regression model was used to analyze the relationship between childhood abuse experiences and depressive symptoms in adolescence. Results: A total of 1 172 students were included in baseline survey, and a follow-up was conducted for 87.1% of them (n=1 021). Among 1 126 students with complete information on childhood abuse experiences at baseline survey, the reported rates of physical, emotional and sexual abuses were 12.8% (144/1 126), 11.1% (125/1 126) and 10.9% (123/1 126), respectively. The prevalence of depressive symptoms at baseline survey and follow-up was 7.0% (82/1 172) and 12.3% (126/1 021), respectively. After adjusted for baseline depressive symptoms, age at follow-up, sex, the only-child in family, household economic status, divorce of parents and BMI, childhood emotional and physical abuse experiences were significant risk factors for depressive symptoms in mid-adolescence, with the ORs were 1.86 (95%CI: 1.03-3.36, P=0.039) and 2.37 (95%CI: 1.39-4.03, P=0.001), respectively. Conclusion: Childhood physical and emotional abuse might increase the risk of depressive symptoms in adolescence.

Developmental characteristics of circadian rhythms in hypothalamic-pituitary-adrenal axis during puberty / 中华流行病学杂志

Objective: To explore the developmental characteristics of circadian rhythms in hypothalamus-pituitary-adrenal (HPA) axis during puberty. Methods: A total of 1 070 students from Grade 2-3 in 3 primary schools in Ma'anshan city, Anhui province, were selected for physical examination and circadian rhythm of HPA axis checked from 2015 to 2017. Saliva samples were collected at each of the following three time points: immediately upon wakening, 30 minutes after wakening and bedtime, with the index of circadian rhythm of HPA axis calculated, which including cortisol awake response (CAR), cortisol in puberty priming and diurnal cortisol slope (DCS). Testicular volume, palpation and visual inspection of breast development were used to assess the state of purbety development on boys and girls. Information on gender, date of birth, time to fall asleep, wake-up time and weekly physical activity were gathered through questionnaire survey. Non-parametric test was used to compare the differences of baseline, follow-up period and different adolescent developmental processes of each index on circadian rhythm of HPA axis. Results: During the period of follow-up program and comparing with the continuous undeveloped group, CAR and the changes of CAR showed significantly increase, both in the puberty priming group and continuous development group, with statistically significant differences (CAR: Z=8.551, 4.680, respectively; P<0.01; the changes of CAR: Z=4.079, 2.700, respectively, P<0.01). There were no significant differences noticed in CAR and the changes of CAR between puberty priming group or continuous development group. The area under the curve (AUC) of cortisol in puberty priming group was slightly higher than that in the persistent undeveloped group (Z=2.591, P=0.010). Both the changes of daily cortisol slope (DCS) in puberty priming group and continuing developed group decreased significantly, when comparing with those in continuous undeveloped group (Z=-2.450, Z=-2.151; all P<0.05). There was no significant difference noticed in the changes of cortisol in puberty priming and DCS between different puberty development stages (the changes of AUC: χ(2)=2.747, P=0.253; DCS: χ(2)=4.554, P=0.032). Conclusions: The indexes of circadian rhythm of HPA axis were associated with the development of puberty. Both the cortisol awakening response and the total amount of diurnal cortisol secretion showed an increase, along with the puberty development. The change of diurnal cortisol slope declined with the development of puberty.

A novel prognostic index for oral cancer in Fujian province / 中华流行病学杂志

Objective: To explore the survival factors and construct a prognostic index (PI) for oral squamous cell carcinoma (OSCC). Methods: From January 2004 to June 2016, a total of 634 patients with pathologically confirmed OSCC were recruited in a hospital of Fujian. The clinical and follow-up data of all the patients with pathologically confirmed OSCC were collected to identify the factors influencing the prognosis of OSCC. All the patients were randomly divided into two groups: modeling group (modeling dataset, n=318) and validation group (validation dataset, n=316). Randomization was carried out by using computer-generated random numbers. In the modeling dataset, survival rates were calculated using Kaplan-Meier method and compared using the log-rank test. Cox regression model was used to estimate the hazard ratio (HRs) and 95% confidence intervals (CIs) of prognosis factors. An PI for OSCC patients prognostic prediction model was developed based on β value of each significant variable obtained from the multivariate Cox regression model. Using the tertile analysis, patients were divided into high-risk group, moderate-risk group, and low-risk group according to the PI, the Akaike information criterion (AIC) and Harrell's c-statistic (C index) were used to evaluated the model's predictability. Results: Results from the multivariate Cox regression model indicated that aged ≥55 years (HR=2.22, 95%CI: 1.45-3.39), poor oral hygiene (HR=2.12, 95%CI: 1.27-3.54), first diagnosis of lymph node metastasis (HR=5.78, 95%CI: 3.60-9.27), TNM stage Ⅲ-Ⅳ (stage Ⅰ as reference) (HR=2.43, 95%CI: 1.10-5.37) and poor differentiation (well differentiation as reference) (HR=2.53, 95%CI: 1.60-4.01) were the risk factors influencing the prognosis of OSCC. The PI model had a high predictability in modeling group and validation group (AIC and C index were 1 205.80, 0.700 2 and 1 150.47, 0.737 3). Conclusion: Age, poor oral hygiene, first diagnosis of lymph node metastasis, TNM stage and histological grade were factors associated with the prognosis of OSCC, and the PI model has a certain significance in the clinical treatment of OSCC.

Can Auxiliary Indicators Improve COVID-19 Forecasting and Hotspot Prediction?

Short-term forecasts of traditional streams from public health reporting (such as cases, hospitalizations, and deaths) are a key input to public health decision-making during a pandemic. Since early 2020, our research group has worked with data partners to collect, curate, and make publicly available numerous real-time COVID-19 indicators, providing multiple views of pandemic activity in the U.S. This paper studies the utility of five such indicators--derived from de-identified medical insurance claims, self-reported symptoms from online surveys, and COVID-related Google search activity--from a forecasting perspective. For each indicator, we ask whether its inclusion in an autoregressive (AR) model leads to improved predictive accuracy relative to the same model excluding it. Such an AR model, without external features, is already competitive with many top COVID-19 forecasting models in use today. Our analysis reveals that (a) inclusion of each of these five indicators improves on the overall predictive accuracy of the AR model; (b) predictive gains are in general most pronounced during times in which COVID cases are trending in "flat" or "down" directions; (c) one indicator, based on Google searches, seems to be particularly helpful during "up" trends.

An Open Repository of Real-Time COVID-19 Indicators

The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from de-identified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data is available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naive baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance StatementThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.