Variation in Cause-Specific Mortality Rates in Italy during the First Wave of the COVID-19 Pandemic: A Study Based on Nationwide Data

Italy was a country severely hit by the first coronavirus disease 2019 (COVID-19) pandemic wave in early 2020. Mortality studies have focused on the overall excess mortality observed during the pandemic. This paper investigates the cause-specific mortality in Italy from March 2020 to April 2020 and the variation in mortality rates compared with those in 2015–2019 regarding sex, age, and epidemic area. Causes of death were derived from the national cause-of-death register. COVID-19 was the leading cause of death among males and the second leading cause among females. Chronic diseases, such as diabetes and hypertensive, ischemic heart, and cerebrovascular diseases, with decreasing or stable mortality rates in 2015–2019, showed a reversal in the mortality trend. Moreover, mortality due to pneumonia and influenza increased. No increase in neoplasm mortality was observed. Among external causes of death, mortality increased for accidental falls but reduced for transport accidents and suicide. Mortality from causes other than COVID-19 increased similarly in both genders and more at ages 65 years or above. Compared with other areas in Italy, the Lombardy region showed the largest excess in mortality for all leading causes. Underdiagnosis of COVID-19 at the beginning of the pandemic may, to some extent, explain the mortality increase for some causes of death, especially pneumonia and other respiratory diseases.

Adapting and validating the log quadratic model to derive under-five age- and cause-specific mortality (U5ACSM): a preliminary analysis

Background The mortality pattern from birth to age five is known to vary by underlying cause of mortality, which has been documented in multiple instances. Many countries without high functioning vital registration systems could benefit from estimates of age- and cause-specific mortality to inform health programming, however, to date the causes of under-five death have only been described for broad age categories such as for neonates (0–27 days), infants (0–11 months), and children age 12–59 months. Methods We adapt the log quadratic model to mortality patterns for children under five to all-cause child mortality and then to age- and cause-specific mortality (U5ACSM). We apply these methods to empirical sample registration system mortality data in China from 1996 to 2015. Based on these empirical data, we simulate probabilities of mortality in the case when the true relationships between age and mortality by cause are known. Results We estimate U5ACSM within 0.1–0.7 deaths per 1000 livebirths in hold out strata for life tables constructed from the China sample registration system, representing considerable improvement compared to an error of 1.2 per 1000 livebirths using a standard approach. This improved prediction error for U5ACSM is consistently demonstrated for all-cause as well as pneumonia- and injury-specific mortality. We also consistently identified cause-specific mortality patterns in simulated mortality scenarios. Conclusion The log quadratic model is a significant improvement over the standard approach for deriving U5ACSM based on both simulation and empirical results.

Community suicide rates and related factors within a surveillance platform in Western Kenya

Background Suicide is an important contributor to the burden of mental health disorders, but community-based suicide data are scarce in many low- and middle-income countries (LMIC) including Kenya. Available data on suicide underestimates the true burden due to underreporting related to stigma and legal restrictions, and under-representation of those not utilizing health facilities. Methods We estimated the cumulative incidence of suicide via verbal autopsies from the Health and Demographic Surveillance System (HDSS) in Kisumu County, Kenya. We then used content analysis of open history forms among deaths coded as accidents to identify those who likely died by suicide but were not coded as suicide deaths. We finally conducted a case-control study of suicides (both verbal autopsy confirmed and likely suicides) compared to accident-caused deaths to assess factors associated with suicide in this HDSS. Results A total of 33 out of 4306 verbal autopsies confirmed suicide as the cause of death. Content analysis of a further 228 deaths originally attributed to accidents identified 39 additional likely suicides. The best estimate of suicide-specific mortality rate was 14.7 per 100,000 population per year (credibility window = 11.3 – 18.0). The most common reported method of death was self-poisoning (54%). From the case-control study interpersonal difficulties and stressful life events were associated with increased odds of suicide in both confirmed suicides and confirmed combined with suspected suicides. Other pertinent factors such as age and being male differed depending upon which outcome was used. Conclusion Suicide is common in this area, and interventions are needed to address drivers. The twofold increase in the suicide-specific mortality rate following incorporation of misattributed suicide deaths exemplify underreporting and misclassification of suicide cases at community level. Further, verbal autopsies may underreport suicide specifically among older and female populations.

Optimal surgical treatment for paratesticular leiomyosarcoma: retrospective analysis of 217 reported cases

Background Paratesticular leiomyosarcoma (LMS) is a rare tumor. Conventionally, tumor resection by high inguinal orchiectomy is performed as the preferred treatment approach for paratesticular sarcoma. On the other hand, testis-sparing surgery has recently attracted attention as a less-invasive treatment option for paratesticular sarcoma. However, the prognostic predictors and optimal treatment strategy for paratesticular LMS remain unclear because of its rarity. In this study, we systematically reviewed previously reported cases of paratesticular LMS to evaluate the prognostic factors and establish the optimal treatment strategy. Methods A systematic search of Medline, Web of Science, Embase, and Google was performed to find articles describing localized paratesticular LMS published between 1971 and 2020 in English. The final cohort included 217 patients in 167 articles. The starting point of this study was the time of definitive surgical treatment, and the end point was the time of local recurrence (LR), distant metastasis (DM), and disease-specific mortality. Results Patients with cutaneous LMS had a slightly better LR-free survival, DM-free survival, and disease-specific survival than those with subcutaneous LMS (p = 0.745, p = 0.033, and p = 0.126, respectively). Patients with higher grade tumors had a significantly higher risk of DM and disease-specific mortality (Grade 3 vs Grade 1 p < 0.001, and Grade 3 vs Grade 1 p < 0.001, respectively). In addition, those with a microscopic positive margin had a significantly higher risk of LR and DM than those with a negative margin (p < 0.001, and p = 0.018, respectively). Patients who underwent simple tumorectomy had a slightly higher risk of LR than those who underwent high inguinal orchiectomy (p = 0.067). Subgroup analysis of cutaneous LMS demonstrated that the difference in LR between simple tumorectomy and high inguinal orchiectomy was limited (p = 0.212). On the other hand, subgroup analysis of subcutaneous LMS revealed a significant difference in LR (p = 0.039). Conclusions Our study demonstrated that subcutaneous LMS and high-grade tumors are prognostic factors for paratesticular LMS. For subcutaneous LMS, tumorectomy with high inguinal orchiectomy should be the optimal treatment strategy to achieve a negative surgical margin.

Construction and validation of the prognostic model for patients with neuroendocrine cervical carcinoma: a competing risk nomogram analysis

Purpose Neuroendocrine cervical carcinoma (NECC) is an uncommon malignancy of the female reproductive system. This study aimed to evaluate cancer-specific mortality and to construct prognostic nomograms for predicting the survival of patients with NECC. Methods we assembled the patients with NECC diagnosed between 2004 to 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Meanwhile, we identified other patients with NECC from the Wenling Maternal and Child Health Care Hospital between 2002 to 2017. Fine and Gray’s test and Kaplan–Meier methods were used to evaluate cancer-specific mortality and overall survival (OS) rates, respectively. Nomograms were constructed for predicting cancer-specific survival (CSS) and OS for patients with NECC. The developed nomograms were validated both internally and externally. Results a total of 894 patients with NECC were extracted from the SEER database, then classified into the training cohort (n = 628) and the internal validation cohort (n = 266). Besides, 106 patients from the Wenling Maternal and Child Health Care Hospital served as an external validation cohort. Nomograms for predicting CSS and OS were constructed on clinical predictors. The validation of nomograms was calculated by calibration curves and concordance indexes (C-indexes). Furthermore, the developed nomograms presented higher areas under the receiver operating characteristic (ROC) curves when compared to the FIGO staging system. Conclusions we established the first competing risk nomograms to predict the survival of patients with NECC. Such a model with high predictive accuracy could be a practical tool for clinicians.