Changes in mortality associated with different hematologic malignancies during the pandemic in the United States.

Patients with hematologic malignancies are at increased risk of adverse COVID-19 outcomes; nonetheless, only sparse population-based data are available on mortality related to hematologic cancers during the pandemic. Number of deaths and age-standardized mortality rates for specific hematologic malignancies selected either as the underlying cause of death (UCOD), or mentioned in death certificates (multiple causes of death-MCOD) were extracted from the US National Center for Health Statistics, CDC WONDER Online Database. Joinpoint analysis was applied to identify changes in mortality trends from 1999 to 2021, and to estimate the annual percent change with 95% Confidence Intervals (CI) across time segments. Among the most common malignancies, chronic lymphocytic leukemia showed marked peaks in the monthly number of deaths attributed to COVID-19 during epidemic waves; acute myeloid leukemia showed the least variation, and non-Hodgkin lymphoma and multiple myeloma were characterized by an intermediate pattern. Age-standardized death rates relying solely on the UCOD did not show significant variations during pandemic years. By contrast, rates based on MCOD increased by 14.0% (CI, 10.2-17.9%) per year for chronic lymphocytic leukemia, by 5.1% (CI, 3.1-7.2%) for non-Hodgkin lymphoma and by 3.2% (CI, 0.3-6.1%) per year for multiple myeloma. Surveillance of mortality based on MCOD is warranted to accurately measure the impact of the COVID-19 pandemic and of other epidemics, including seasonal flu, on patients with hematologic malignancies, and to assess the effects of vaccination campaigns and other preventive measures.

Adenoma Detection Rate and Colorectal Cancer Risk in Fecal Immunochemical Test Screening Programs : An Observational Cohort Study.

BACKGROUND: Colorectal cancer (CRC) screening programs based on fecal immunochemical tests (FITs) represent the standard of care for population-based interventions. Their benefit depends on the identification of neoplasia at colonoscopy after FIT positivity. Colonoscopy quality measured by adenoma detection rate (ADR) may affect screening program effectiveness. OBJECTIVE: To examine the association between ADR and postcolonoscopy CRC (PCCRC) risk in a FIT-based screening program. DESIGN: Retrospective population-based cohort study. SETTING: Fecal immunochemical test-based CRC screening program between 2003 and 2021 in northeastern Italy. PATIENTS: All patients with a positive FIT result who had a colonoscopy were included. MEASUREMENTS: The regional cancer registry supplied information on any PCCRC diagnosed between 6 months and 10 years after colonoscopy. Endoscopists' ADR was categorized into 5 groups (20% to 39.9%, 40% to 44.9%, 45% to 49.9%, 50% to 54.9%, and 55% to 70%). To examine the association of ADR with PCCRC incidence risk, Cox regression models were fitted to estimate hazard ratios (HRs) and 95% CIs. RESULTS: Of the 110 109 initial colonoscopies, 49 626 colonoscopies done by 113 endoscopists between 2012 and 2017 were included. After 328 778 person-years follow-up, 277 cases of PCCRC were diagnosed. Mean ADR was 48.3% (range, 23% and 70%). Incidence rates of PCCRC from lowest to highest ADR group were 13.13, 10.61, 7.60, 6.01, and 5.78 per 10 000 person-years. There was a significant inverse association between ADR and PCCRC incidence risk, with a 2.35-fold risk increase (95% CI, 1.63 to 3.38) in the lowest group compared with the highest. The adjusted HR for PCCRC associated with 1% increase in ADR was 0.96 (CI, 0.95 to 0.98). LIMITATION: Adenoma detection rate is partly determined by FIT positivity cutoff; exact values may vary in different settings. CONCLUSION: In a FIT-based screening program, ADR is inversely associated with PCCRC incidence risk, mandating appropriate colonoscopy quality monitoring in this setting. Increasing endoscopists' ADR may significantly reduce PCCRC risk. PRIMARY FUNDING SOURCE: None.

Systemic lupus erythematosus incidence and prevalence in a large population-based study in northeastern Italy.

OBJECTIVES: We aimed at estimating the incidence and prevalence of SLE in northeastern Italy over the period 2012-20. METHODS: A retrospective population-based study was conducted in Veneto Region (4.9 million people) using the population registry, an administrative health database where all residents are recorded. Between 2012 and 2020, SLE prevalence was defined by a healthcare co-payment exemption for SLE (national registry code 028) or any hospital diagnosis of SLE (International Classification of Disease , Ninth Revision, Clinical Modification 710.0), whichever came first. Incident SLE was defined from 2013 to 2020 to exclude prevalent cases. Standardized incidence and prevalence rates were reported by age and sex. RESULTS: During the study period, we identified 4283 SLE patients (85% female), with 1092 incident cases. Across the study period, SLE standardized point prevalence increased from 63.5 (95% CI 61.2, 65.8) to 70.6 (95% CI 68.3, 73.0) per 100 000 residents, corresponding to an annual increment of 1.14% (P < 0.0001). The highest prevalence was observed in females aged 60-69 years. SLE incidence corresponded to 2.8 per 100 000 person-years (95% CI 2.6, 2.9), with an annual decline of 7.3% (P < 0.0001). Incidence was 5-fold higher in females (female-to-male incidence rate ratio: 5.00, 95% CI 4.25, 5.87; P < 0.0001), with a peak among women aged 30-39 years. At diagnosis, women were significantly younger (45 years, IQR 33-58) than men (52 years, IQR 38-64). CONCLUSIONS: Over the last decade, SLE prevalence has increased, while incidence has stably declined. In view of the introduction of new high-cost drugs, a clear definition of the epidemiology of SLE is crucial for all healthcare stakeholders.

Association of multiple-sclerosis-related mortality with COVID-19 and other common infections: a multiple causes of death analysis.

BACKGROUND AND PURPOSE: People with multiple sclerosis (MS) suffer from higher infection-related mortality compared to the general population; however, sparse data are available on the increased risk of death associated with coronavirus disease 2019 (COVID-19) and other common types of infections. METHODS: All mortality records and multiple-cause-of-death data in 2010-2021 of residents in the Veneto region (northeastern Italy) were extracted. Mention of specific infections was compared between death certificates reporting MS or not. Odds ratios (OR) with 95% confidence intervals (95% CI) were estimated by conditional logistic regression matching by age, sex and calendar year. The bimonthly averages of MS-related deaths in 2010-2019 were compared with those registered during the pandemic (2020-2021). RESULTS: Of 580,015 deaths through 2010-2021, MS was mentioned in 850 cases (0.15%), 59.3% women. Influenza and pneumonia were reported in 18.4% of MS-related compared to 11.0% non-MS-related deaths (OR 2.72, 95% CI 2.28-3.25). The odds of mention of urinary tract infections was significantly greater in MS-related deaths of men (OR 8.16, 95% CI 5.23-12.7) than women (OR 3.03, 95% CI 1.82-5.02). Aspiration pneumonia, pressure ulcers/skin infections and sepsis were also significantly associated with MS-related deaths. Reporting of COVID-19 as a cause of death did not significantly differ between deaths with and without mention of MS (approximately 11% of both). However, compared to 2010-2019, peaks in MS-related deaths were observed during the pandemic waves. CONCLUSIONS: Infections continue to play a significant role in MS-related deaths, underlying the need to improve prevention and management strategies.

Veneto Region dementia-related mortality during the COVID-19 pandemic: multiple causes of death and time series analysis.

BACKGROUND: Older individuals with dementia have been severely affected by the COVID-19 pandemic. There is a lack of in-depth evaluation of mortality trends using both the underlying cause of death (UCOD) and the multiple causes of death (MCOD) approaches. The objective of this study was to determine the impact of the COVID-19 pandemic on dementia-related deaths considering comorbidities and the place of death. METHODS: This retrospective, population-based study was conducted in Veneto, Italy. All the death certificates of individuals aged ≥65 years issued from 2008 to 2020 were analyzed for dementia-related mortality using age-standardized sex-stratified rates of dementia as UCOD and MCOD. Excess in monthly dementia-related mortality in 2020 was estimated by applying Seasonal Autoregressive Integrated Moving Average (SARIMA) model. RESULTS: Overall, 70 301 death certificates reported dementia (MCOD proportional mortality: 12.9%), and 37 604 cases identified it as UCOD (proportional mortality: 6.9%). In 2020, the MCOD proportional mortality increased to 14.3% whereas that of UCOD remained static (7.0%). Compared to the SARIMA prediction, MCOD increased by 15.5% in males and 18.3% in females in 2020. Compared to the 2018-19 average, deaths in nursing homes increased by 32% in 2020, at home by 26% and in hospitals by 12%. CONCLUSIONS: An increase in dementia-related mortality during the first months of the COVID-19 pandemic could only be detected using the MCOD approach. MCOD proved to be more robust, and hence, should be included in future analyses. Nursing homes appeared to be the most critical setting which should guide establishing protective measures for similar situations.

Perfluoroalkyl substances and thyroid stimulating hormone levels in a highly exposed population in the Veneto Region.

BACKGROUND: Per- and poly-fluoroalkyl substances (PFAS) are persistent and widespread environmental pollutants. People living in Veneto Region (Italy) have been exposed from the late 1970s to 2013 to elevated concentrations of PFAS through drinking water. The effect of PFAS on thyroid function is still controversial and studies focusing on thyroid stimulating hormone (TSH) have shown inconsistent results. The aim of this study was to evaluate the association between serum PFAS and TSH levels and its dose-response relationship in a large population of highly exposed individuals. METHODS: A cross-sectional study was conducted on 21,424 individuals aged 14-39 living in the contaminated area. In the main analysis, participants with prevalent thyroid disease and pregnant women were excluded. Serum levels of perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorohexanesulfonic acid (PFHxS) and perfluorononanoic acid (PFNA) were measured. Generalized Additive Models were used to evaluate the association between TSH levels and serum PFAS, using thin plate spline smooth terms to model the potential non-linear relationship. Models were stratified by sex and age group and adjusted for potential confounders. A secondary analysis was conducted to evaluate the association between PFAS with prevalent self-reported thyroid disorders. RESULTS: We found no association between TSH and any type of PFAS among adolescents or women. A decrease in TSH concentration was observed in association with an IQR increase in PFHxS and a mild decrease in TSH at low levels of PFOA, PFOS and PFHxS among male adults. Self-reported thyroid disease was more common among women with higher levels of PFNA concentrations, whereas all other PFAS were not associated with thyroid diseases regardless of sex or age. CONCLUSIONS: Overall there is no evidence of an association between TSH and PFAS. However, some results are suggestive of a possible inverse association of TSH with PFOA, PFOS and PFHxS among adult males.

Epidemiology of traumatic spinal cord injury: a large population-based study.

STUDY DESIGN: A retrospective population-based study. OBJECTIVES: Describe the incidence of traumatic spinal cord injury (TSCI) and mortality risks, based on the characteristics of the patient, anatomical level of the lesion, setting/cause of the injury, and type of healthcare support received within the regional trauma network (highly specialized trauma center or spoke hospital). SETTING: Between 2011 and 2020, 1303 patients with incident TSCI were identified in a population of 4.9 million inhabitants. METHODS: Hospital discharge records and mortality records were used to identify patients and outcomes. Cox regression models were fitted to estimate mortality risks across several subgroups. RESULTS: Over the past decade, age-sex-standardized TSCI incidence rates remained stable with 26.5 cases (95% CI, 25.0-27.9) per 1,000,000 inhabitants (mean age 59.2 years) and most cases were males (68.3%). Incidence was directly associated with age while the male to female ratio was inversely related. Most TSCIs were cervical lesions (52.1%), and the most common cause of injury were traffic crashes (29.9%) followed by occupational accidents (29.8%). Sex, cause of the trauma, or inpatient hospital management were not associated with an increased risk of death. Mortality rates were greater for cervical lesions, and increased with age, remaining stably high among older individuals even 12 months after the accident. One-month mortality risk was significantly higher at ≥75 years compared to <55 years (adjusted HR 9.14 (95% CI, 4.17-20.03)). CONCLUSION: Public health policies should aim at reducing preventable TSCIs, and special attention should be drawn to long-term management of elderly patients in the attempt to decrease mortality rates.

[Impact of COVID-19 on the immigrant population in the Veneto Region (Northern Italy), by geographical area of origin]. / Impatto del COVID-19 nella popolazione immigrata in Veneto, per area geografica di provenienza.

OBJECTIVES: to examine the differences in SARS-CoV-2 infection and hospitalization rates among migrant populations in Veneto Region (Northern Italy), according to the geographic area of origin. SETTING AND PARTICIPANTS: all residents in Veneto Region aged <65 years were included in the analyses. All subjects infected by SARS-CoV-2 and hospitalized for COVID-19 were identified by means of the regional biosurveillance system. MAIN OUTCOME MEASURES: age- and gender-specific infection and hospitalization rates were stratified by geographic area of origin and were estimated using the number of incident cases over the resident population in Veneto on 01.01.2021. Incidence rate ratios (IRR) for infection and hospitalization rates were estimated using a Poisson model, adjusted for age and gender, among migrants compared to Italians. RESULTS: compared to Italians, SARS-CoV-2 infection rates were significantly higher among migrants from Central and South America and Central and South Asia, lower among those from North Africa and High-Income Countries (HIC), and were approximately halved for those coming from Other Asian Countries (mainly represented by China). Hospitalization rates were significantly higher for all migrant populations when compared to Italians, with the exception of those coming from HIC. Neither age nor gender seemed to modify the association of the geographic area of origin with SARS-CoV-2 infection and hospitalization rates. IRR for SARS-CoV-2 infection of migrants compared to Italians showed how migrants from Other Asian Countries had the lowest infection rates (-53%), followed by people from HIC (-25%), North Africa (-21%), and Eastern Europe (-10%). Higher infection rates were present for Central and South America and Central and South Asia (+17% and +10, respectively). Hospitalization rates were especially high among migrants from Central and South Asia, Africa, and Central and South America, ranging from 1.84 to 3.14 times those observed for Italians. CONCLUSIONS: a significant heterogeneity in SARS-CoV-2 infection and hospitalization rates of migrant populations from different geographic areas of origin were observed. The significantly lower incidence rate ratio for infections, compared to that observed for hospitalizations, is suggestive of a possible under-diagnosis of SARS-CoV-2 infection among migrant populations. Public health efforts should be targeted at increasing support among migrants to contrast the spread of the pandemic by potentiating vaccination campaigns, contact tracing, and COVID-19 diagnostic tests.

Association Between Age at Diabetes Onset and Subsequent Risk of Dementia.

Importance: Trends in type 2 diabetes show an increase in prevalence along with younger age of onset. While vascular complications of early-onset type 2 diabetes are known, the associations with dementia remains unclear. Objective: To determine whether younger age at diabetes onset is more strongly associated with incidence of dementia. Design, Setting, and Participants: Population-based study in the UK, the Whitehall II prospective cohort study, established in 1985-1988, with clinical examinations in 1991-1993, 1997-1999, 2002-2004, 2007-2009, 2012-2013, and 2015-2016, and linkage to electronic health records until March 2019. The date of final follow-up was March 31, 2019. Exposures: Type 2 diabetes, defined as a fasting blood glucose level greater than or equal to 126 mg/dL at clinical examination, physician-diagnosed type 2 diabetes, use of diabetes medication, or hospital record of diabetes between 1985 and 2019. Main Outcomes and Measures: Incident dementia ascertained through linkage to electronic health records. Results: Among 10 095 participants (67.3% men; aged 35-55 years in 1985-1988), a total of 1710 cases of diabetes and 639 cases of dementia were recorded over a median follow-up of 31.7 years. Dementia rates per 1000 person-years were 8.9 in participants without diabetes at age 70 years, and rates were 10.0 per 1000 person-years for participants with diabetes onset up to 5 years earlier, 13.0 for 6 to 10 years earlier, and 18.3 for more than 10 years earlier. In multivariable-adjusted analyses, compared with participants without diabetes at age 70, the hazard ratio (HR) of dementia in participants with diabetes onset more than 10 years earlier was 2.12 (95% CI, 1.50-3.00), 1.49 (95% CI, 0.95-2.32) for diabetes onset 6 to 10 years earlier, and 1.11 (95% CI, 0.70-1.76) for diabetes onset 5 years earlier or less; linear trend test (P < .001) indicated a graded association between age at onset of type 2 diabetes and dementia. At age 70, every 5-year younger age at onset of type 2 diabetes was significantly associated with an HR of dementia of 1.24 (95% CI, 1.06-1.46) in analyses adjusted for sociodemographic factors, health behaviors, and health-related measures. Conclusions and Relevance: In this longitudinal cohort study with a median follow-up of 31.7 years, younger age at onset of diabetes was significantly associated with higher risk of subsequent dementia.

A Systematic Review of Case-Identification Algorithms Based on Italian Healthcare Administrative Databases for Three Relevant Diseases of the Nervous System: Parkinson's Disease, Multiple Sclerosis, and Epilepsy.

BACKGROUND: Parkinson's Disease (PD), Multiple Sclerosis (MS), and Epilepsy are three highly impactful health conditions affecting the nervous system. PD, MS, and epilepsy cases can be identified by means of Healthcare Administrative Databases (HADs) to estimate the occurrence of these diseases, to better monitor the adherence to treatments, and to evaluate patients' outcomes. Nevertheless, the absence of a validated and standardized approach makes it hard to quantify case misclassification. OBJECTIVES: to identify and describe all PD, MS, and epilepsy case-identification algorithms by means of Italian HADs, through the review of papers published in the past 10 years. METHODS: this study is part of a project that systematically reviewed case-identification algorithms for 18 acute and chronic conditions by means of HADs in Italy. PubMed was searched for original articles, published between 2007 and 2017, in Italian or English. The search string consisted of a combination of free text and MeSH terms with a common part that focused on HADs and a disease-specific part. All identified papers were screened by two independent reviewers. Pertinent papers were classified according to the objective for which the algorithm had been used, and only articles that used algorithms for primary objectives (I disease occurrence; II population/cohort selection; III outcome identification) were considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms have been reported. Further information on specific objective(s), accuracy measures, sensitivity analyses and the contribution of each HAD, have also been recorded. RESULTS: the search strategy led to the identification of 70 papers for PD, 154 for MS, and 100 for epilepsy, of which 3 papers for PD, 6 for MS, and 5 for epilepsy were considered pertinent. Most articles were published in the last three years (2014-2017) and focused on a region-wide setting. Out of all pertinent articles, 3 original algorithms for PD, 4 for MS, and 4 for epilepsy were identified. The Drug Prescription Database (DPD) and Hospital Discharge record Database (HDD) were used by almost all PD, MS, and epilepsy case-identification algorithms. The Exemption from healthcare Co-payment Database (ECD) was used by all PD and MS case-identification algorithms, while only 1 epilepsy case-identification algorithm used this source. All epilepsy case-identification algorithms were based on at least a combination of electroencephalogram (EEG) and drug prescriptions. An external validation had been performed by 2 papers for MS, 2 for epilepsy, and only 1 for PD. CONCLUSION: the results of our review highlighted the scarce use of HADs for the identification of cases affected by neurological diseases in Italy. While PD and MS algorithms are not so heterogeneous, epilepsy case-identification algorithms have increased in complexity over time. Further validations are needed to better understand the specific characteristics of these algorithms.

A Systematic Review of Case-Identification Algorithms Based on Italian Healthcare Administrative Databases for Two Relevant Diseases of the Respiratory System: Asthma and Chronic Obstructive Pulmonary Disease.

OBJECTIVES: to identify and describe all asthma and Chronic Obstructive Pulmonary Disease (COPD) case-identification algorithms by means of Italian Healthcare Administrative Databases (HADs), through the review of papers published in the past 10 years. METHODS: this study is part of a project that systematically reviewed case-identification algorithms for 18 acute and chronic conditions by means of HADs in Italy. PubMed was searched for original articles, published between 2007 and 2017, in Italian or English. The search string consisted of a combination of free text and MeSH terms with a common part that focused on HADs and a disease-specific part. All identified papers were screened by two independent reviewers; exclusion criteria were the following: no description of reported algorithms, algorithm developed outside of the Italian context, exclusive use of death certificates, pathology register, general practitioner or pediatrician data. Pertinent papers were classified according to the objective for which the algorithm had been used, and only articles that used algorithms for primary objectives (I disease occurrence; II population/cohort selection; III outcome identification) were considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms have been reported. Further information on specific objective(s), accuracy measures, sensitivity analyses and the contribution of each HAD, have also been recorded. RESULTS: the search string led to the identification of 98 and 147 papers, respectively for asthma and COPD. By screening the references, 2 papers for asthma and 7 for COPD were added. At the end of the screening process, 14 pertinent papers were identified for asthma and 31 for COPD. Half of these used healthcare data covering a time period between 2008 and 2014. More than 75% considered the age range 6-17 for asthma and >=45 for COPD. About one-third of the articles used algorithms to estimate the occurrence of these diseases. Fourteen algorithms for asthma and 16 for COPD were extracted from the papers and characterized. The Drug Prescription Database (DPD) was used by almost all asthma case-identification algorithms, while only 7 COPD algorithms used this data source. The spectrum of active ingredients was strongly overlapping between the two diseases, with different combinations of drugs and administration routes, as well as specific number of prescriptions, follow-back years, and age ranges. Age class and chronic treatment were the main disease-specific traits that emerged from the algorithms. Three external validation processes have been performed for asthma and three for COPD. High accuracy levels have been found for asthma. COPD sensitivity analyses were unsatisfactory, while a high specificity was found for algorithms based on hospital discharge records. CONCLUSION: elements from the review on the use of healthcare administrative databases represent a useful tool to decide which algorithm to adopt, based on the algorithm's individual requirements, limits, and accuracy, taking into account the specific research objective.

A Systematic Review of Case-Identification Algorithms for 18 Conditions Based on Italian Healthcare Administrative Databases: A Study Protocol.

BACKGROUND: there has been a long-standing, consistent use worldwide of Healthcare Administrative Databases (HADs) for epidemiological purposes, especially to identify acute and chronic health conditions. These databases are able to reflect health-related conditions at a population level through disease-specific case-identification algorithms that combine information coded in multiple HADs. In Italy, in the past 10 years, HAD-based case-identification algorithms have experienced a constant increase, with a significant extension of the spectrum of identifiable diseases. Besides estimating incidence and/or prevalence of diseases, these algorithms have been used to enroll cohorts, monitor quality of care, assess the effect of environmental exposure, and identify health outcomes in analytic studies. Despite the rapid increase in the use of case-identification algorithms, information on their accuracy and misclassification rate is currently unavailable for most conditions. OBJECTIVES: to define a protocol to systematically review algorithms used in Italy in the past 10 years for the identification of several chronic and acute diseases, providing an accessible overview to future users in the Italian and international context. METHODS: PubMed will be searched for original research articles, published between 2007 and 2017, in Italian or English. The search string consists of a combination of free text and MeSH terms with a common part on HADs and a disease-specific part. All identified papers will be screened for eligibility by two independent reviewers. All articles that used/defined an algorithm for the identification of each disease of interest using Italian HADs will be included. Algorithms with exclusive use of death certificates, pathology register, general practitioner or pediatrician data will be excluded. Pertinent papers will be classified according to the objective for which the algorithm was used, and only articles that used algorithms with "primary objectives" (I disease occurrence; II population/cohort selection; III outcome identification) will be considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms will be collected. Further information on specific accuracy measures from external validations, sensitivity analyses, and the contribution of each source will be recorded. This protocol will be applied for 16 different systematic reviews concerning eighteen diseases (Hypothyroidism, Hyperthyroidism, Diabetes mellitus, Type 1 diabetes mellitus, Acute myocardial infarction, Ischemic heart disease, Stroke, Hypertension, Heart failure, Congenital heart anomalies, Parkinson's disease, Multiple sclerosis, Epilepsy, Chronic obstructive pulmonary disease, Asthma, Inflammatory bowel disease, Celiac disease, Chronic kidney failure). CONCLUSION: this protocol defines a standardized approach to extensively examine and compare all experiences of case identification algorithms in Italy, on the 18 abovementioned diseases. The methodology proposed may be applied to other systematic reviews concerning diseases not included in this project, as well as other settings, including international ones. Considering the increasing availability of healthcare data, developing standard criteria to describe and update characteristics of published algorithms would be of great use to enhance awareness in the choice of algorithms and provide a greater comparability of results.

Changes in cancer-related mortality during the COVID-19 pandemic in the United States.

Few studies have examined cancer-related mortality overall, never mind select cancer types, during the COVID-19 pandemic. Data on cancer-related mortality (any mention in death certificates, multiple causes of death approach) was extracted from the US Centers for Disease Control and Prevention WONDER database. Changes in trends for age-standardized mortality rates through 1999-2021 were assessed by Joinpoint analysis. In total, 1 379 643 cancer-related deaths were registered in 2020-2021, with cancer selected as the underlying cause in 88%. After 2 decades of decline, age-standardized cancer-related mortality increased from 2019 to 2021 for all cancers (annual percentage change = 1.6%, 95% confidence interval = 0.6% to 2.6%), especially for prostate cancer (annual percentage change = 5.1%, 95% confidence interval = 2.2% to 8.2%) and hematologic cancers (annual percentage change = 4.8%, 95% confidence interval = 3.1% to 6.6%). Sharp peaks in cancer-related deaths for many cancer sites were observed during pandemic waves in both 2020 and 2021, mostly attributed to COVID-19 as the underlying cause. Multiple causes of death analyses are warranted to fully assess the impact of the pandemic on cancer-related mortality.

Traumatic brain injury incidence and mortality: a large population-based study.

BACKGROUND: Traumatic brain injury (TBI) is a severe condition that represents a major global public health concern. OBJECTIVES: Provide a comprehensive epidemiological outlook encompassing TBI incidence, healthcare provision and mortality. METHODS: Population-based study in Veneto (4.9 million inhabitants), Italy, from 2012 to 2021. Hospital discharge and mortality records were used to assess incidence and mortality. Kaplan-Meier survival estimator and Cox regression models were fitted to investigate determinants of mortality. RESULTS: Between 2012 and 2021, there were 37,487 incident TBI cases, corresponding to an age-standardized rate of 77.30/100,000 people (95% CI 76.52-78.09), higher among males, with an exponential growth after age 70. Leading causes were domestic (33.1%) and traffic accidents (17.7%), the first predominating among the elderly and children, while the latter in males 15-24 and older people. After rates stably declined between 2012 and 2019, the study captured a sharp decrease especially for traffic and occupational accidents in males, due to COVID-19 lockdown in 2020. Overall, 48.9% TBI patients were hospitalized in a specialized trauma center, with 2.6% requiring a transfer after accessing a spoke hospital. Over a 3.7 years median follow-up, 16,145 deaths were recorded, with higher mortality for those undergoing neurosurgical interventions, regardless of their access point. Risks of death increased with age, male gender, and comorbidities. DISCUSSION: TBI incidence is characterized by distinct patterns, affecting particularly older individuals and males. Minimal hospital transfers with comparable survival irrespective of access point suggests an effective patient management within the network. The study underscores the critical need for acute-phase support and prolonged care strategies for older TBI patients.

Sepsis-related mortality: long-term trends in Northeastern Italy, including pandemic years.

BACKGROUND: Global estimates of sepsis mortality are based on multiple causes of death (MCOD, any mention of the condition on death certificates); however, MCOD data are sparse and mainly referring to the pre-pandemic period. OBJECTIVES: To investigate recent trends in sepsis-related mortality, associated sites of infection, and comorbidities in Veneto (Northeastern Italy). METHODS: Mortality records from 2008 to 2022 were extracted, and sepsis-related mortality was assessed based both on the underlying cause of death (UCOD) and on MCOD. The average annual percent change in age-standardised rates was estimated by join point regression through the whole study period. MCOD records were investigated to retrieve infection sites and comorbidities. RESULTS: Sepsis was mentioned in 63,479 death certificates, growing from 4.9% out of all deaths in 2008 to 12.9% in 2022. Age-standardised mortality rates increased yearly by 8.2% (95%CI 2.1-14.7%) based on the UCOD and by 5.9% (95%CI 5.3-6.5%) based on MCOD. Sharp peaks in monthly mortality were observed in correspondence with flu epidemics, COVID-19 pandemic waves, and periods of extreme heat. The percentage of sepsis-related deaths associated to urinary tract infections, and with mention of neurodegenerative disorders and chronic kidney disease increased over time. CONCLUSION: Raised awareness of physicians, ageing of the population, spread of antimicrobial resistance further fuelled by the COVID-19 pandemic are among reasons of increasing sepsis-related mortality in Italy. Continuous monitoring of sepsis by means of MCOD data and other surveillance tools is warranted.

Adherence to Cervical Cancer Screening Programs in Migrant Populations: A Systematic Review and Meta-Analysis.

Organized cervical cancer screening programs to promote the early identification of precancerous lesions have proven to be effective in decreasing the burden associated with cervical cancer, but knowledge regarding screening adherence among migrant women compared to that of native women has not been summarized. A systematic search of the literature on PubMed, Scopus and Embase led to the identification of 772 papers that were published up to July 2022 and reported population-based data regarding adherence to cervical screening. The screening participation rates among migrant women, compared to native women, were pooled using a random-effects meta-analysis. A total of 18 papers were included in the review, with most of them being conducted in Europe (83.3%). Overall, migrants showed a significantly lower participation rate compared to native women (OR for screening adherence: 0.54, 95% CI = 0.42-0.70). This discrepancy was especially evident for migrant women from North Africa and Sub-Saharan Africa (OR = 0.47, 95% CI = 0.35-0.63, and OR = 0.35, 95% CI = 0.24-0.49, respectively). The results of this systematic review emphasize the importance of increasing cervical cancer screening adherence among migrant women. A significant heterogeneity in screening adherence was observed based on the country of origin. Interventions aimed at reducing the disparities in screening participation should specifically consider how to improve the recruitment of migrant women.