Background: The Coronavirus disease 2019 (COVID-19) pandemic has been a great burden on the health care system. It has also had a great impact on other public health issues, including cancer screening. Delayed cancer screening was also noticed in the U.S, which may have led to both delayed diagnosis and poor prognosis. In Taiwan, population-based cancer screening for breast cancer, oral cancer, colon cancer and cervical cancer has been executed for years. Method: In this study we have analyzed the change in screening numbers during the period of 2019 to 2021 during COVID-19 outbreak in Taiwan. Result: Through our results we found that total cancer screening numbers decreased from 307,547 to 103,289 (66% decrease) from the years 2020 to 2021. There was a 63%, 79%, 65% and 71% decrease in screening cases for colon cancer, oral cancer, cervical cancer and breast cancer, respectively during that period. A similar condition was noticed when comparing 2019 to 2021 when the disclosed total cancer screening numbers decreased by 70% (2019-2021); 65%, 83%, 70% and 76% in colon cancer, oral cancer, cervical cancer and breast cancer, respectively. Among these various cancer screenings, oral cancer screening showed the greatest reduction rate. We also compared the reduction rates taken from different regions in Taiwan. It was in Taipei, where most COVID-19 cases were noted, that the greatest reduction rate of cancer screening numbers occurred. A proportional decrease of screening cases was also noticed in all areas when confirmed COVID-19 cases rose. Conclusion: Screening for cancers has dropped significantly due to the pandemic and its effect on long-term health needs to be evaluated. Additionally, efforts should be taken to address this cancer screening number deficit which has taken place during the COVID-19 pandemic.

Several dimensional impairments regarding Comprehensive Geriatric Assessment (CGA) have been shown to be associated with the prognosis of older patients. The purpose of this study is to investigate mortality prediction factors based upon clinical characteristics and test in CGA, and then subsequently develop a prediction model to classify both short- and long-term mortality risk in hospitalized older patients after discharge. A total of 1565 older patients with a median age of 81 years (74.0–86.0) were consecutively enrolled. The CGA, which included assessment of clinical, cognitive, functional, nutritional, and social parameters during hospitalization, as well as clinical information on each patient was recorded. Within the one-year follow up period, 110 patients (7.0%) had died. Using simple Cox regression analysis, it was shown that a patient’s Length of Stay (LOS), previous hospitalization history, admission Barthel Index (BI) score, Instrumental Activity of Daily Living (IADL) score, Mini Nutritional Assessment (MNA) score, and Charlson’s Comorbidity Index (CCI) score were all associated with one-year mortality after discharge. When these parameters were dichotomized, we discovered that those who were aged ≥90 years, had a LOS ≥ 12 days, an MNA score < 17, a CCI ≥ 2, and a previous admission history were all independently associated with one-year mortality using multiple cox regression analyses. By applying individual scores to these risk factors, the area under the receiver operating characteristics curve (AUC) was 0.691 with a cut-off value score ≧ 3 for one year mortality, 0.801 for within 30-day mortality, and 0.748 for within 90-day mortality. It is suggested that older hospitalized patients with varying risks of mortality may be stratified by a prediction model, with tailored planning being subsequently implemented.