Decline in Cancer Diagnoses during the 'Zero COVID' Policy in Hong Kong: Indirect Spillover Impact of the COVID-19 Pandemic.

AIMS: Despite a largely successful 'zero COVID' policy in 2020, the COVID-19 pandemic disrupted routine cancer services in the city of Hong Kong. The aims of this study were to examine the trends in cancer incidence before and during the COVID-19 pandemic and estimate missed cancer diagnoses. MATERIALS AND METHODS: We used population-based data from the Hong Kong Cancer Registry 1983-2020 to examine the trends of age- and sex-standardised cancer incidence before and during the COVID-19 pandemic. We applied: (i) the annual average percentage change (AAPC) calculated using the Joinpoint regression model and (ii) the autoregressive integrated moving average (ARIMA) model to forecast cancer incidence rates in 2020. Missed cancer diagnoses in 2020 were estimated by comparing forecasted incidence rates to reported rates. A subgroup analysis was conducted by sex, age and cancer site. RESULTS: The cancer incidence in Hong Kong declined by 4.4% from 2019 to 2020 (male 8.1%; female 1.1%) compared with the long-term AAPC of 0.5% from 2005 to 2019 (95% confidence interval 0.3, 0.7). The gap between the reported and forecasted incidence for 2020 ranged from 5.1 to 5.7% (male 8.5%, 9.8%; female 2.3%, 3.5%). We estimated 1525-1596 missed cancer diagnoses (ARIMA estimate -98, 3148; AAPC 514, 1729) in 2020. Most missed diagnoses were in males (ARIMA 1361 [327, 2394]; AAPC 1401 [1353, 1460]), with an estimated 479-557 missed cases of colorectal cancer (ARIMA 112, 837; AAPC 518, 597) and 256-352 missed cases of prostate cancer (AAPC 231, 280; ARIMA 110, 594). CONCLUSION: The incidence of new cancer diagnoses declined in 2020 contrary to the long-term increase over the previous decades. Significantly lower diagnoses than expected were observed in males, particularly for colorectal and prostate cancers. Fewer reported cancer cases indicate missed diagnoses and could lead to delayed treatment that could impact future health outcomes.

Elevated risk of multimorbidity post-COVID-19 infection: protective effect of vaccination.

BACKGROUND: It is unclear how the coronavirus disease 2019 (Covid-19) pandemic has affected multimorbidity incidence among those with one pre-existing chronic condition, as well as how vaccination could modify this association. AIM: To examine the association of Covid-19 infection with multimorbidity incidence among people with one pre-existing chronic condition, including those with prior vaccination. DESIGN: Nested case-control study. METHODS: We conducted a territory-wide nested case-control study with incidence density sampling using Hong Kong electronic health records from public healthcare facilities and mandatory Covid-19 reports. People with one listed chronic condition (based on a list of 30) who developed multimorbidity during 1 January 2020-15 November 2022 were selected as case participants and randomly matched with up to 10 people of the same age, sex and with the same first chronic condition without having developed multimorbidity at that point. Conditional logistic regression was used to estimate adjusted odds ratios (aORs) of multimorbidity. RESULTS: In total, 127 744 case participants were matched with 1 230 636 control participants. Adjusted analysis showed that there were 28%-increased odds of multimorbidity following Covid-19 [confidence interval (CI) 22% to 36%] but only 3% (non-significant) with prior full vaccination with BNT162b2 or CoronaVac (95% CI -2% to 7%). Similar associations were observed in men, women, older people aged 65 or more, and people aged 64 or younger. CONCLUSIONS: We found a significantly elevated risk of multimorbidity following a Covid-19 episode among people with one pre-existing chronic condition. Full vaccination significantly reduced this risk increase.

Cardiovascular diseases among diffuse large B-cell lymphoma long-term survivors in Asia: a multistate model study.

BACKGROUND: We modeled the clinical course of a cohort of diffuse large B-cell lymphoma (DLBCL) patients with no prior cardiovascular diseases (CVDs) using a multistate modeling framework. PATIENTS AND METHODS: Data on 2600 patients with DLBCL diagnosed between 2000 and 2018 and had received chemotherapy with or without radiotherapy were obtained from a population-wide electronic health database of Hong Kong. We used the Markov illness-death model to quantify the impact of doxorubicin and various risk factors (therapeutic exposure, demographic, comorbidities, cardiovascular risk factors, and lifestyle factors which included smoking) on the clinical course of DLBCL (transitions into incident CVD, lymphoma death, and other causes of death). RESULTS: A total of 613 (23.6%) and 230 (8.8%) of 2600 subjects died of lymphoma and developed incident CVD, respectively. Median follow-up was 7.0 years (interquartile range 3.8-10.8 years). Older ages [hazard ratio (HR) for >75 versus ≤60 years 1.88; 95% confidence interval (CI) 1.25-2.82 and HR for 61-75 versus ≤60 years 1.60; 95% CI 1.12-2.30], hypertension (HR 4.92; 95% CI 2.61-9.26), diabetes (HR 1.43; 95% CI 1.09-1.87), and baseline use of aspirin (HR 5.30; 95% CI 3.93-7.16) were associated with an increased risk of incident CVD. In a subgroup of anticipated higher-risk patients (aged 61-75 years, smoked, had diabetes, and received doxorubicin), we found that they remained on average 7.9 (95% CI 7.2-8.8) years in the DLBCL state and 0.1 (95% CI 0.0-0.4) years in the CVD state, if they could be followed up for 10 years. The brief time in the CVD state is consistent with the high chance of death in patients who developed CVD. Other causes of death have overtaken DLBCL-related death after about 5 years. CONCLUSIONS: In this Asian population-based cohort, we found that incident CVDs can occur soon after DLBCL treatment and continued to occur throughout survivorship. Clinicians are advised to balance the risks and benefits of treatment choices to minimize the risk of CVD.

Short- and potential long-term adverse health outcomes of COVID-19: a rapid review.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in millions of patients infected worldwide and indirectly affecting even more individuals through disruption of daily living. Long-term adverse outcomes have been reported with similar diseases from other coronaviruses, namely Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Emerging evidence suggests that COVID-19 adversely affects different systems in the human body. This review summarizes the current evidence on the short-term adverse health outcomes and assesses the risk of potential long-term adverse outcomes of COVID-19. Major adverse outcomes were found to affect different body systems: immune system (including but not limited to Guillain-Barré syndrome and paediatric inflammatory multisystem syndrome), respiratory system (lung fibrosis and pulmonary thromboembolism), cardiovascular system (cardiomyopathy and coagulopathy), neurological system (sensory dysfunction and stroke), as well as cutaneous and gastrointestinal manifestations, impaired hepatic and renal function. Mental health in patients with COVID-19 was also found to be adversely affected. The burden of caring for COVID-19 survivors is likely to be huge. Therefore, it is important for policy makers to develop comprehensive strategies in providing resources and capacity in the healthcare system. Future epidemiological studies are needed to further investigate the long-term impact on COVID-19 survivors.

Prediction models for the risk of cardiovascular diseases in Chinese patients with type 2 diabetes mellitus: a systematic review.

OBJECTIVES: Diabetes mellitus (DM) is a serious public health issue worldwide, and DM patients have higher risk of cardiovascular diseases (CVDs), which is the leading cause of DM-related deaths. China has the largest DM population, yet a robust model to predict CVDs in Chinese DM patients is still lacking. This systematic review is carried out to summarize existing models and identify potentially important predictors for CVDs in Chinese DM patients. STUDY DESIGN: Systematic review. METHODS: Medline and Embase were searched for data from April 1st, 2011 to May 31st, 2018. A study was eligible if it developed CVD (defined as total CVD or any major cardiovascular component) risk prediction models or explored potential predictors of CVD specifically for Chinese people with type 2 DM. Standardized forms were utilized to extract information, appraise applicability, risk of bias, and availabilities. RESULTS: Five models and 29 studies focusing on potential predictors were identified. Models for a primary care setting, or to predict total CVD, are rare. A number of common predictors (e.g. age, sex, diabetes duration, smoking status, glycated hemoglobin (HbA1c), blood pressure, lipid profile, and treatment modalities) were observed in existing models, in which urine albumin:creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) are highly recommended for the Chinese population. Variability of blood pressure (BP) and HbA1c should be included in prediction model development as novel factors. Meanwhile, interactions between age, sex, and risk factors should also be considered. CONCLUSIONS: A 10-year prediction model for CVD risk in Chinese type 2 DM patients is lacking and urgently needed. There is insufficient evidence to support the inclusion of other novel predictors in CVDs risk prediction functions for routine clinical use.

How are family doctors serving the Hong Kong community during the COVID-19 outbreak? A survey of HKCFP members.

INTRODUCTION: This study evaluated the preparedness of family doctors during the early phase of the coronavirus disease 2019 (COVID-19) outbreak in Hong Kong. METHODS: All members of the Hong Kong College of Family Physicians were invited to participate in a cross-sectional online survey using a 20-item questionnaire to collect information on practice preparedness for the COVID-19 outbreak through an email followed by a reminder SMS message between 31 January 2020 and 3 February 2020. RESULTS: Of 1589 family doctors invited, 491 (31%) participated in the survey, including 242 (49%) from private sector. In all, 98% surveyed doctors continued to provide clinical services during the survey period, but reduced clinic service demands were observed in 45% private practices and 24% public clinics. Almost all wore masks during consultation and washed hands between or before patient contact. Significantly more private than public doctors (80% vs 26%, P<0.001) experienced difficulties in stocking personal protective equipment (PPE); more public doctors used guidelines to manage suspected patients. The main concern of the respondents was PPE shortage. Respondents appealed for effective public health interventions including border control, quarantine measures, designated clinic setup, and public education. CONCLUSION: Family doctors from public and private sectors demonstrated preparedness to serve the community from the early phase of the COVID-19 outbreak with heightened infection control measures and use of guidelines. However, there is a need for support from local health authorities to secure PPE supply and institute public health interventions.

Feature tracking for assessment of diastolic function by cardiovascular magnetic resonance imaging.

AIM: To assess the agreement of cardiovascular magnetic resonance imaging (CMRI) feature-tracking (FT) parameters with echocardiography to diagnose diastolic dysfunction; to determine whether a similar parameter to mitral inflow early diastolic velocity to early diastolic tissue velocity ratio (E/e') can increase accuracy of imaging by dividing the phase contrast (PC) mitral inflow E-wave (E) with a CMRI-FT parameter; to compare the agreement between CMRI-FT and PC diastolic function assessment using echocardiography. MATERIALS AND METHODS: Patients (n=71; 43 abnormal diastolic function) undergoing both CMRI and echocardiography independently were included. Echocardiography was the reference standard. CMRI-FT analysed the short and long axis cine contours. PC images of mitral inflow, tissue velocity, pulmonary vein flow, and left atrial area were assessed. RESULTS: Using CMRI-FT, the area under the curve (AUC) for identifying diastolic dysfunction was >0.80 for radial and circumferential strain, systolic strain rate (SSR), and early diastolic strain rate (DSR). For cases with CMRI-determined left ventricular ejection fraction (LVEF) ≥50% (n=38), circumferential DSR was the only parameter with good accuracy (AUC=0.87; cut-off 0.93/s). E/circumferential DSR ratio and longitudinal strain had high accuracy in all patients (AUC=0.88 and 0.93 respectively) and CMRI-determined LVEF ≥50% (AUC=0.81; cut-off 76.7). Circumferential DSR showed the highest agreement with echocardiography (higher than E/circumferential DSR and PC assessment) in all cases (kappa 0.75; p<0001) and cases with CMRI LVEF ≥50% (kappa 0.73; p<0.0001). CONCLUSIONS: CMRI-FT circumferential DSR showed the highest accuracy for determining diastolic dysfunction with good agreement with echocardiography. Circumferential DSR had higher accuracy than E/circumferential DSR and PC.

Relation between HbA1c and incident cardiovascular disease over a period of 6 years in the Hong Kong population.

AIM: The current trend on diabetes management advocates replacing the paradigm from a uniform to an individualized patient-centered haemoglobin A1c (HbA1c) target, but there is no consensus on the optimal HbA1c level. The study aimed at examining the association between HbA1c and the risk of cardiovascular diseases (CVD) for diabetic patients with different characteristics, in order to identify patient-centered treatment targets. METHODS: A retrospective cohort study was conducted on 115,782 Chinese adult primary care patients with type 2 diabetes mellitus (DM) but no known CVD history, who were prescribed antidiabetic medications in 2010-2011. The cumulative mean HbA1c over a median follow-up period of 5.8 years was used to evaluate the relationship between HbA1c and CVD incidence using Cox analysis. Subgroup analyses were conducted by stratifying different baseline characteristics including gender, age, smoking status, diabetes duration, body mass index, Charlson's comorbidity index and DM treatment modalities. RESULTS: For patients with a DM duration of<2years, an exponential relationship between HbA1c and risk of CVD was identified, suggesting that there was no threshold HbA1c level for CVD risk. For other diabetic patients, an HbA1c level of 6.8-7.2% was associated with a minimum risk for CVD and a J-shaped curvilinear association between HbA1c. The risk of CVD increased in patients with HbA1c<6.5% or ≥7.5%. CONCLUSION: Among Chinese primary care patients at the early (<2years) disease stage, lower HbA1c targets (<6.5%) may be warranted to prevent CVD events whilst for all others, excessively lower HbA1c levels may not necessarily better and can potentially be harmful.