This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.

https://acsjournals.onlinelibrary.wiley.com/doi/pdf/10.3322/caac.21660

Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population‐based cancer occurrence and outcomes. Incidence data (through 2018) were collected by the Surveillance, Epidemiology, and End Results program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2019) were collected by the National Center for Health Statistics. In 2022, 1,918,030 new cancer cases and 609,360 cancer deaths are projected to occur in the United States, including approximately 350 deaths per day from lung cancer, the leading cause of cancer death. Incidence during 2014 through 2018 continued a slow increase for female breast cancer (by 0.5% annually) and remained stable for prostate cancer, despite a 4% to 6% annual increase for advanced disease since 2011. Consequently, the proportion of prostate cancer diagnosed at a distant stage increased from 3.9% to 8.2% over the past decade. In contrast, lung cancer incidence continued to decline steeply for advanced disease while rates for localized‐stage increased suddenly by 4.5% annually, contributing to gains both in the proportion of localized‐stage diagnoses (from 17% in 2004 to 28% in 2018) and 3‐year relative survival (from 21% to 31%). Mortality patterns reflect incidence trends, with declines accelerating for lung cancer, slowing for breast cancer, and stabilizing for prostate cancer. In summary, progress has stagnated for breast and prostate cancers but strengthened for lung cancer, coinciding with changes in medical practice related to cancer screening and/or treatment. More targeted cancer control interventions and investment in improved early detection and treatment would facilitate reductions in cancer mortality.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.3322/caac.21708

Cancer statistics, 2022

Importance The coronavirus disease 2019 (COVID-19) pandemic, due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19. Observations SARS-CoV-2 is spread primarily via respiratory droplets during close face-to-face contact. Infection can be spread by asymptomatic, presymptomatic, and symptomatic carriers. The average time from exposure to symptom onset is 5 days, and 97.5% of people who develop symptoms do so within 11.5 days. The most common symptoms are fever, dry cough, and shortness of breath. Radiographic and laboratory abnormalities, such as lymphopenia and elevated lactate dehydrogenase, are common, but nonspecific. Diagnosis is made by detection of SARS-CoV-2 via reverse transcription polymerase chain reaction testing, although false-negative test results may occur in up to 20% to 67% of patients; however, this is dependent on the quality and timing of testing. Manifestations of COVID-19 include asymptomatic carriers and fulminant disease characterized by sepsis and acute respiratory failure. Approximately 5% of patients with COVID-19, and 20% of those hospitalized, experience severe symptoms necessitating intensive care. More than 75% of patients hospitalized with COVID-19 require supplemental oxygen. Treatment for individuals with COVID-19 includes best practices for supportive management of acute hypoxic respiratory failure. Emerging data indicate that dexamethasone therapy reduces 28-day mortality in patients requiring supplemental oxygen compared with usual care (21.6% vs 24.6%; age-adjusted rate ratio, 0.83 [95% CI, 0.74-0.92]) and that remdesivir improves time to recovery (hospital discharge or no supplemental oxygen requirement) from 15 to 11 days. In a randomized trial of 103 patients with COVID-19, convalescent plasma did not shorten time to recovery. Ongoing trials are testing antiviral therapies, immune modulators, and anticoagulants. The case-fatality rate for COVID-19 varies markedly by age, ranging from 0.3 deaths per 1000 cases among patients aged 5 to 17 years to 304.9 deaths per 1000 cases among patients aged 85 years or older in the US. Among patients hospitalized in the intensive care unit, the case fatality is up to 40%. At least 120 SARS-CoV-2 vaccines are under development. Until an effective vaccine is available, the primary methods to reduce spread are face masks, social distancing, and contact tracing. Monoclonal antibodies and hyperimmune globulin may provide additional preventive strategies. Conclusions and Relevance As of July 1, 2020, more than 10 million people worldwide had been infected with SARS-CoV-2. Many aspects of transmission, infection, and treatment remain unclear. Advances in prevention and effective management of COVID-19 will require basic and clinical investigation and public health and clinical interventions.

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Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review.

Summary
This report describes the epidemiology, burden, and treatment of osteoporosis in the 27 countries of the European Union (EU27).

/pdf/osteoporosis-in-the-european-union-medical-management-5gi5e439ck.pdf

Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA).

Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study.

Risk prediction models are potentially useful tools for health practitioners and policy makers. When new predictors are proposed to add to existing models, the improvement of discrimination is one of the main measures to assess any increment in performance. In assessing such predictors, we observed two paradoxes: 1) the discriminative ability within all individual risk strata was worse than for the overall population; 2) incremental discrimination after including a new predictor was greater within each individual risk strata than for the whole population. We show two examples of the paradoxes and analyse the possible causes. The key cause of bias is use of the same prediction model as for both stratifying the population, and as the base model to which the new predictor is added.

Analyses within risk strata overestimate gain in discrimination: the example of coronary artery calcium scores

label extension. Br J Dermatol 2020; 182:85–96. 5 Broeders JA, Ahmed Ali U, Fischer G. Systematic review and metaanalysis of randomized clinical trials (RCTs) comparing topical calcineurin inhibitors with topical corticosteroids for atopic dermatitis: a 15-year experience. J Am Acad Dermatol 2016; 75:410–9. 6 Akinlade B, Guttman-Yassky E, de Bruin-Weller M et al. Conjunctivitis in dupilumab clinical trials. Br J Dermatol 2019; 181:459–73. 7 Bakker DS, Ariens LFM, van Luijk C et al. Goblet cell scarcity and conjunctival inflammation during treatment with dupilumab in patients with atopic dermatitis. Br J Dermatol 2019; 180:1248–9. 8 Silverberg J. Revolutionizing atopic dermatitis. Cutis 2019; 104:142–3. 9 Armenta AM, Jaquez SD, Levy ML, Diaz LZ. Use of psychologic strategies to reduce pain and anxiety related to dermatology procedures. Pediatr Dermatol 2019; 36:416–17. 10 Blauvelt A, Simpson EL, Tyring SK et al. Dupilumab does not affect correlates of vaccine-induced immunity: a randomized, placebocontrolled trial in adults with moderate-to-severe atopic dermatitis. J Am Acad Dermatol 2019; 80:158–67. 11 Nguyen HL, Anderson KR, Tollefson MM. New and emerging therapies for pediatric atopic dermatitis. Paediatr Drugs 2019; 21:239–60.

Causal inference in melanoma epidemiology using Mendelian randomization.

Experiential Teaching for Public Health Practice

https://onlinelibrary.wiley.com/doi/pdf/10.5694/mja2.50907

How to use imperfect tests for COVID-19 (SARS-CoV-2) to make clinical decisions.

We support the need to carefully evaluate different starting and stopping ages and different intervals for programs of screening mammography. Dr Patel’s analysis, however, is fatally flawed by classic screening biases—length bias, the extreme of which is called overdiagnosis bias, and lead time bias. These biases have long been known to invalidate comparisons of 5-year survival rates between screened and unscreened women [1-4]. Taking the complement of 5-year survival, by subtraction from 100% to produce 5-year mortalities, does nothing to overcome these biases. Length bias results from the selection effect of screening whereby regular screenings disproportionately detect slowly progressing cancers. These slow-growing cancers have a higher probability of detection because of their long preclinical duration. Because slowly progressing cancers will have a better prognosis (reflected in higher 5-year survival and lower 5-year mortality) than rapidly progressing cancers, length bias is one reason why these statistics do not reflect true mortality benefits for screening-detected cases. Much of the difference in stage distribution (and mortality) between the annual program and biennial programs seen in Table 1 and Figure 1 may be explained by greater length bias associated with the greater number of screens in the annual program. Lead time bias is the second reason that 5-year survival (or mortality) rates mislead. The clock starts ticking from the date of

Katy J.L. Bell

Papers

Analyses within risk strata overestimate gain in discrimination: the example of coronary artery calcium scores

Causal inference in melanoma epidemiology using Mendelian randomization.

Experiential Teaching for Public Health Practice

How to use imperfect tests for COVID-19 (SARS-CoV-2) to make clinical decisions.

Demonstration of Classic Screening Biases, Not Additional Benefit of Annual Over Biennial Screening.