Implications for cancer care in Iran during COVID-19 pandemic

Evaluation of the effect of the COVID-19 pandemic on the all-cause, cause-specific mortality, YLL, and life expectancy in the first 2 years in an Iranian population-an ecological study

Background

COVID-19 pandemic resulted in excess mortality and changed the trends of causes of death worldwide. In this study, we investigate the all-cause and cause-specific deaths during the COVID-19 pandemic (2020-2022) compared to the baseline (2018-2020), considering age groups, gender, place of residence, and place of death in south Khorasan, east of Iran.

Methods

The present ecological study was conducted using South Khorasan Province death certificate data during 2018-2022. The number of death and all-cause and cause-specific mortality rates (per 100,000 people) were calculated and compared based on age groups, place of residence, place of death, and gender before (2018-2020) and during the COVID-19 pandemic (2020-2022). We also calculated total and cause-specific years of life lost (YLL) to death and gender-specific life expectancy at birth.

Results

A total of 7,766 deaths occurred from March 21, 2018, to March 20, 2020 (pre-pandemic) and 9,984 deaths from March 21, 2020, to March 20, 2022 (pandemic). The mean age at death increased by about 2 years during the COVID-19 pandemic. The mortality rate was significantly increased in the age groups 20 years and older. The most excess deaths were recorded in men, Aged more than 60 years, death at home, and the rural population. Mortality due to COVID-19 accounted for nearly 17% of deaths. The highest increase in mortality rate was observed due to endocrine and Cardiovascular diseases. Mortality rates due to the genitourinary system and Certain conditions originating in the perinatal period have decreased during the COVID-19 pandemic. The major causes of death during the pandemic were Cardiovascular diseases, COVID-19, cancer, chronic respiratory diseases, accidents, and endocrine diseases in both sexes, in rural and urban areas. Years of life lost (YLL) increased by nearly 15.0%, which was mostly due to COVID-19, life expectancy at birth has steadily declined from 2018 to202 for both genders (from 78.4 to 75).

Conclusion

In this study, we found that All-cause mortality increased by 25.5% during the COVID-19 pandemic, especially in men, older adult, Rural residents, and those who died at home (outside the hospital). Considering that the most common causes of death during the COVID-19 pandemic are also non-communicable diseases. It is necessary to pay attention to non-communicable diseases even during the pandemic of a serious infectious disease like COVID-19. The years of life lost also increased during the COVID-19 pandemic, which is necessary to pay attention to all age groups, especially the causes of death in young people. In most developing countries, the first cause of death of these groups is accidents.

Five-Class Classification of Cervical Pap Smear Images: A Study of CNN-Error-Correcting SVM Models

Objectives

Different complex strategies of fusing handcrafted descriptors and features from convolutional neural network (CNN) models have been studied, mainly for two-class Papanicolaou (Pap) smear image classification. This paper explores a simplified system using combined binary coding for a five-class version of this problem.

Methods

This system extracted features from transfer learning of AlexNet, VGG19, and ResNet50 networks before reducing this problem into multiple binary sub-problems using error-correcting coding. The learners were trained using the support vector machine (SVM) method. The outputs of these classifiers were combined and compared to the true class codes for the final prediction.

Results

Despite the superior performance of VGG19-SVM, with mean ± standard deviation accuracy and sensitivity of 80.68% ± 2.00% and 80.86% ± 0.45%, respectively, this model required a long training time. There were also false-negative cases using both the VGGNet-SVM and ResNet-SVM models. AlexNet-SVM was more efficient in terms of running speed and prediction consistency. Our findings also showed good diagnostic ability, with an area under the curve of approximately 0.95. Further investigation also showed good agreement between our research outcomes and that of the state-of-the-art methods, with specificity ranging from 93% to 100%.

Conclusions

We believe that the AlexNet-SVM model can be conveniently applied for clinical use. Further research could include the implementation of an optimization algorithm for hyperparameter tuning, as well as an appropriate selection of experimental design to improve the efficiency of Pap smear image classification.

A multi-institutional assessment of COVID-19-related risk in radiation oncology

PURPOSE

The COVID-19 pandemic has presented challenges to delivering safe and timely care for cancer patients. The oncology community has undertaken substantial workflow adaptations to reduce transmission risk for patients and providers. While various control measureshave been proposed and implemented, little is known about their impact on safety of the radiation oncology workflow and potential for transmission. The objective of this study was to assess potential safety impacts of control measures employed during the COVID-19 pandemic.

METHODS

A multi-institutional study was undertaken to assess the risks of pandemic-associated workflow adaptations using failure mode and effects analysis (FMEA). Failure modes were identified and scored using FMEA formalism. FMEA scores were used to identify highest-risk aspects of the radiation therapy process. The impact of control measures on overall risk was quantified. Agreement among institutions was evaluated.

RESULTS

Thirty three failure modes and 22 control measures were identified. Control measures resulted in risk score reductions for 22 of the failure modes, with the largest reductions from screening of patients and staff, requiring use of masks, and regular cleaning of patient areas. The median risk score for all failure modes was reduced from 280 to 168. There was high institutional agreement for 90.3% of failure modes but only 47% of control measures.

CONCLUSIONS

COVID-related risks are similar across oncology practices in this study. While control measures can reducerisk, their use varied. The effectiveness of control measures on risk may guide selection of the highest-impact workflow adaptions to ensure safe care in oncology.

Discordance of COVID-19 guidelines for patients with cancer: A systematic review

This review was aimed to systematically evaluate the available literature on the impact of COVID-19 on cancer care and to critically analyze the diagnostic and therapeutic strategies suggested by various healthcare providers, societies, and institutions. Majority guidelines for various types of cancers favored a delay in treatment or a nonsurgical approach wherever feasible. These guidelines are based on a low level of evidence and have significant discordance for the role and timing of surgery, especially in early tumors.

Cancer and SARS-CoV-2 Infection: Diagnostic and Therapeutic Challenges

In late December 2019, a new infectious viral disease appeared. A new betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), has been recognized as the pathogen responsible for this infection. Patients affected by tumors are more vulnerable to infection owing to poor health status, concomitant chronic diseases, and immunosuppressive conditions provoked by both the cancer and antitumor therapies. In this review, we have analyzed some lesser known aspects of the relationship between neoplasms and SARS-CoV-2 infection, starting from the different expression of the ACE2 receptor of the virus in the various neoplastic pathologies, and the roles that different cytokine patterns could have in vulnerability to infection and the appearance of complications. This review also reports the rationale for a possible use of drugs commonly employed in neoplastic therapy, such as bevacizumab, ibrutinib, selinexor, thalidomide, carfilzomib, and PD-1 inhibitors, for the treatment of SARS-CoV-2 infection. Finally, we have highlighted some diagnostic challenges in the recognition of SARS-CoV-2 infection in cancer-infected patients. The combination of these two health problems-tumors and a pandemic virus-could become a catastrophe if not correctly handled. Careful and judicious management of cancer patients with SARS-Cov-2 could support a better outcome for these patients during the current pandemic.

Evolution of clinical radiotherapy physics practice under COVID-19 constraints

As the COVID-19 spread continues to challenge the societal and professional norms, radiotherapy around the globe is pushed into an unprecedented transformation. We will discuss how clinical physics has transformed to ascertain safety and quality standards across four facilities around the world through diversity of action, innovation, and scientific flexibility.