The impact of COVID-19 pandemic course in the number and severity of hospitalizations for other natural causes in a large urban center in Brazil

The COVID-19 pandemic may indirectly impact hospitalizations for other natural causes. Belo Horizonte is a city with 2.5 million inhabitants in Brazil, one of the most hardly-hit countries by the pandemic, where local authorities monitored hospitalizations daily to guide regulatory measures. In an ecological, time-series study, we investigated how the pandemic impacted the number and severity of public hospitalizations by other natural causes in the city, during 2020. We assessed the number and proportion of intensive care unit (ICU) admissions and in-hospital deaths for all-natural causes, COVID-19, non-COVID-19 natural causes, and four disease groups: infectious, respiratory, cardiovascular, and neoplasms. Observed data from epidemiological week (EW) 9 (first diagnosis of COVID-19) to EW 48, 2020, was compared to the mean for the same EW of 2015–2019 and differences were tested by Wilcoxon rank-sum test. The five-week moving averages of the studied variables in 2020 were compared to that of 2015–2019 to describe the influence of regulatory measures on the indicators. During the studied period, there was 54,722 hospitalizations by non-COVID-19 natural causes, representing a 28% decline compared to the previous five years (p<0.001). There was a concurrent significant increase in the proportion of ICU admissions and deaths. The greater reductions were simultaneous to the first social distancing decree or occurred in the peak of COVID-19 hospitalizations, suggesting different drivers. Hospitalizations by specific causes decreased significantly, with greater increase in ICU admissions and deaths for infectious, cardiovascular, and respiratory diseases than for neoplasms. While the first reduction may have resulted from avoidance of contact with healthcare facilities, the second reduction may represent competing causes for hospital beds with COVID-19 after reopening of activities. Health policies must include protocols to address hospitalizations by other causes during this or future pandemics, and a plan to face the rebound effect for elective deferred procedures.

Causes of long-term mortality in patients with head and neck squamous cell carcinomas

Purpose After treatment of a head and neck squamous cell carcinoma (HNSCC), patients with an adequate control of the tumor have a decreased overall survival when compared to age- and gender-matched controls in the general population. The aim of our study was to analyze the causes of long-term mortality in patients with HNSCC. Methods We carried out a retrospective study of 5122 patients with an index HNSCC treated at our center between 1985 and 2018. We analyzed the survival considering three causes of death: mortality associated with the HNSCC index tumor, mortality associated with a second or successive neoplasm, and mortality associated with a non-cancer cause. Results After the diagnosis of an HNSCC the most frequent cause of death is the head and neck tumor itself during the first 3.5 years of follow-up. Thereafter, mortality is more frequently associated with competing causes of death, such as second malignancies and non-cancer causes. Mortality associated with second and successive neoplasms was 2.3% per year, a percentage that was maintained constant throughout the follow-up. Likewise, mortality attributable to non-cancer causes was 1.6% per year, which also remained constant. There were differences in the mortality patterns according to the characteristics of the patients. Conclusion There are differences in the mortality patterns of patients with HNSCC depending on their characteristics. Knowledge of these patterns can help in the design of guidelines to improve the follow-up protocols of this group of patients to optimize the clinical cost-effectiveness.

Incidence and Risk Factors for Cerebrovascular-Specific Mortality in Patients with Colorectal Cancer: A Registry-Based Cohort Study Involving 563298 Patients

Background: Colorectal cancer (CRC) is one of the most prevalent diseases and the second leading cause of death worldwide. However, the relationship between CRC and cerebrovascular-specific mortality (CVSM) remains elusive and less is known about the influencing factors associated with CVSM in CRC. Here, we aimed to analyze the incidence as well as the risk factors of CVSM in CRC. Methods: Patients with a primary CRC diagnosed between 1973 and 2015 were identified from Surveillance Epidemiology and End Results database with follow-up data available until 31 December 2016. Conditional standardized mortality ratios were calculated to compare the incidence of CVSM between CRC patients and the general US population. Univariate and multivariate survival analyses with a competing risk model were used to interrogate the risk factors for CVSM. Results: A total of 563298 CRC individuals were included. The CVSM in CRC patients was significantly higher than the general population in all age subgroups. Among competing causes of death in patients, the cumulative mortality caused by cerebrovascular-specific diseases steadily increased during study period. While age and surgery positively influenced CVSM on both univariate and multivariate analyses, male patients and those who had radiotherapy, chemotherapy, more recent year (2001-2015) of diagnosis as well as multiple primary or distant tumors experienced a lower risk of CVSM. Interpretation: Our data suggest a potential role for CRC in the incidence of CVSM and also identify several significant predictors of CVSM, which may be helpful for risk stratification and therapeutic optimization of cerebrovascular-specific diseases in CRC patients.

Cause of Death in Patients in Radiation Oncology

BackgroundThe accurate attribution of death in oncologic patients is a difficult task. The patient’s death is often attributed to his or her underlying cancer and therefore judged as cancer-related. We hypothesized that even though our patient’s cancers were either advanced or metastatic, not all patients had died simply because of their cancer.MethodsA total of 105 patients were included in this retrospective analysis. Patient data were collected from digital and paper-based records. Cause of death was assessed from death certificate and compared to the medical autopsy reports. Discrepancies between premortem and postmortem diagnoses were classified as class I and II discrepancies.ResultsOf 105 patients included, autopsy consent was obtained in 56 cases (53%). Among them, 32 of 56 were palliatively sedated, and 42/56 patients died cancer-related as confirmed by autopsy. The most common cause of death by autopsy report was multiorgan failure followed by a combination of tumor and infection, predominantly lung cancer with pneumonia. Here, 21/56 cases (37%) showed major missed diagnoses: seven cases showed class I, 10 class II, and both discrepancies. The most commonly missed diagnoses in both categories were infections, again mainly pneumonia.ConclusionsCancer was the leading cause of death in our study population. A quarter of the patients, however, did not die due to their advanced or metastatic cancers but of potentially curable causes. We therefore conclude that it is important to consider competing causes of death when treating palliative cancer patients. In a palliative setting, the treatment of a potentially curable complication should be discussed with the patients and their families in a shared decision-making process. From our experience, many patients will decline treatment or even further diagnostics when given the option of best supportive care.

An Alternative Promotion Time Cure Model with Overdispersed Number of Competing Causes: An Application to Melanoma Data

A cure rate model under the competing risks setup is proposed. For the number of competing causes related to the occurrence of the event of interest, we posit the one-parameter Bell distribution, which accommodates overdispersed counts. The model is parameterized in the cure rate, which is linked to covariates. Parameter estimation is based on the maximum likelihood method. Estimates are computed via the EM algorithm. In order to compare different models, a selection criterion for non-nested models is implemented. Results from simulation studies indicate that the estimation method and the model selection criterion have a good performance. A dataset on melanoma is analyzed using the proposed model as well as some models from the literature.

Epileptic seizures in multiple sclerosis: prevalence, competing causes and diagnostic accuracy

Background Multiple sclerosis (MS) is accompanied by an increased risk of epileptic seizures, but data with a detailed description of the competing causes are lacking. Methods We aimed to describe a cohort of patients with both MS and epileptic seizures in a retrospective, population-based study. Results We included 59 out of 2285 MS patients who had at least one epileptic seizure. Out of them, 22 had seizures before the diagnosis of MS, whereas epileptic seizures occurred after MS diagnosis in 37 patients, resulting in a total prevalence of epileptic seizures in MS of 2.6%. Competing causes could be found in 50.8% (30/59) of all patients, with 40.9% (9/22) compared to 56.8% (21/37) of the MS patients with seizures before vs after MS diagnosis. The main alternative causes were traumatic brain injury and cerebral ischemia accounting for more than 30% of the patients, with no difference between the subgroups. 33.3% and 55.6% of MS patients with seizures before/after MS diagnosis had documented pathological EEG alterations. Conclusion A remarkable percentage of MS patients with epileptic seizures do have alternative competing causes at the time of the first seizure. A detailed diagnostic setup including patient history, EEG and MRI is recommended in the evaluation and choice for the best treatment.