COVID-19 and Cancer: Acting on past lessons and learning new ones

eLife has published a special issue containing articles that examine how cancer prevention, control, care and survivorship were impacted by the COVID-19 pandemic.
  1. Eduardo L Franco  Is a corresponding author
  2. Diane M Harper  Is a corresponding author
  1. eLife, United Kingdom

We have seen much new science emerge since January 2020, when the World Health Organization (WHO) declared COVID-19 to be a public health emergency of international concern. Indeed, according to PubMed, researchers have published more than 420,000 articles on COVID-19, SARS-CoV-2 and related topics to date. Moreover, a number of efficacious and safe vaccines and anti-virals were developed in a relatively short period of time. Researchers from many different fields – including virology, epidemiology, molecular biology, vaccinology, and infectious disease modelling – were involved in these efforts.

For those who worked on the global HIV/AIDS epidemic, which began in 1981, the COVID-19 pandemic brought a sense of déjà vu. Back in the early 1980s, with the support of funding agencies, entire academic teams in a wide range of fields reoriented their research programs in an effort to control the effects of the HIV/AIDS epidemic via multiple areas, including epidemiology, HIV pathogenesis, vaccine development, diagnostics and therapy. Four decades later, HIV infection is no longer a death sentence, but there is still a need for research into new treatments and approaches for prevention and disease management, and to ensure that existing treatments are made available to vulnerable populations in low- and middle-income countries. The HIV/AIDS epidemic also resulted in a great deal of new science (almost 500,000 articles), albeit spread out over a longer time frame than the articles published on COVID-19 to date.

There are other parallels. Much like the HIV/AIDS epidemic required new science, new social practices, and new disease-management skills, so did the COVID pandemic. The COVID-19 lockdowns resulted in the suspension of cancer-prevention activities (such as tobacco control and vaccinations for hepatitis B and human papillomavirus) and prevented people in many countries from being screened for cancer. Treatments for patients with newly diagnosed cancers were also delayed, and existing patients – who were already at increased risk of death from the combined comorbidity of their cancer and COVID – had their oncology surgeries postponed. At the same time, like all other patients, cancer patients had to share their physicians with large numbers of COVID-19 patients: the pandemic also led to high levels of stress and burnout among medical staff, which has resulted in many leaving the profession. Understanding the impact of the pandemic on the entire trajectory of cancer – prevention, screening, diagnosis, therapy, survivorship, and end-of-life care – will help us plan interventions and prioritize care to mitigate or prevent the increases in cancer burden that may happen in the medium and long term.

There are also parallels in how the public and politicians responded to HIV/AIDS and COVID-19. Much like we learned to fight the pervasive bigotry that marginalized gay communities in the 1980s, we must learn how to fight the misinformation and disinformation that have hindered efforts to prevent the spread of COVID-19 in many countries. One stark difference between HIV/AIDS and COVID-19 is that we still do not have an effective vaccine against HIV.

The articles included in this special issue cover many different aspects of the impact of the COVID-19 pandemic on cancer across the globe, including both high- and low-income regions and countries. Many of the articles report the results of empirical research studies that captured the extent of the disruptions in care (such as disruptions in screening and vaccination activities, and delays in diagnoses and care). There are also articles about therapeutic interventions for the care of cancer patients affected by COVID-19, and articles about insightful modelling studies that provided projections of the impact of the pandemic on cancer prevention, control, and care pathways.

One of the lessons learned during the pandemic was that cancer control programmes could be made more resilient by taking advantage of recent technological advances: examples of this include the wider use of patient-centred screening for a number of cancers. The pandemic also confirmed the usefulness of videoconferencing for many different activities, including telemedicine, university teaching and virtual clinical appointments.

We thank all the reviewing editors, guest editors and reviewers who were involved in the peer review of the articles in this special issue (their names are on the home page for the special issue and/or in the individual articles), and we hope that it will serve as a valuable source of scientific evidence and information for those working in public health and elsewhere to develop plans to respond to future epidemics and pandemics. We also hope that this collection of articles will be a valuable historical account of what was often an improvised – yet innovative – response to a major public health threat.

Four decades after the start of the HIV/AIDS epidemic, HIV infection and AIDS are still with us. It is likely that SARS-CoV-2 and COVID-19 – and their successors – will also be with us for years to come, and that they will continue to inspire research that can be translated to provide new medicines, diagnostics and treatments. As the articles in this special issue confirm, it is essential that this research also includes work on managing cancer risk during any future public health emergency.

Article and author information

Author details

  1. Eduardo L Franco

    Eduardo L Franco is a Senior Editor at eLife

    For correspondence
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4409-8084
  2. Diane M Harper

    Diane M Harper is a Deputy Editor at eLife

    For correspondence
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7648-883X

Publication history

  1. Version of Record published: September 6, 2023 (version 1)


© 2023, Franco and Harper

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.


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  1. Eduardo L Franco
  2. Diane M Harper
COVID-19 and Cancer: Acting on past lessons and learning new ones
eLife 12:e91607.

Further reading

    1. Biochemistry and Chemical Biology
    2. Epidemiology and Global Health
    Takashi Sasaki, Yoshinori Nishimoto ... Yasumichi Arai
    Research Article

    Background: High levels of circulating adiponectin are associated with increased insulin sensitivity, low prevalence of diabetes, and low body mass index (BMI); however, high levels of circulating adiponectin are also associated with increased mortality in the 60-70 age group. In this study, we aimed to clarify factors associated with circulating high-molecular-weight (cHMW) adiponectin levels and their association with mortality in the very old (85-89 years old) and centenarians.

    Methods: The study included 812 (women: 84.4%) for centenarians and 1,498 (women: 51.7%) for the very old. The genomic DNA sequence data were obtained by whole genome sequencing or DNA microarray-imputation methods. LASSO and multivariate regression analyses were used to evaluate cHMW adiponectin characteristics and associated factors. All-cause mortality was analyzed in three quantile groups of cHMW adiponectin levels using Cox regression.

    Results: The cHMW adiponectin levels were increased significantly beyond 100 years of age, were negatively associated with diabetes prevalence, and were associated with SNVs in CDH13 (p = 2.21 × 10-22) and ADIPOQ (p = 5.72 × 10-7). Multivariate regression analysis revealed that genetic variants, BMI, and high-density lipoprotein cholesterol (HDLC) were the main factors associated with cHMW adiponectin levels in the very old, whereas the BMI showed no association in centenarians. The hazard ratios for all-cause mortality in the intermediate and high cHMW adiponectin groups in very old men were significantly higher rather than those for all-cause mortality in the low level cHMW adiponectin group, even after adjustment with BMI. In contrast, the hazard ratios for all-cause mortality were significantly higher for high cHMW adiponectin groups in very old women, but were not significant after adjustment with BMI.

    Conclusions: cHMW adiponectin levels increased with age until centenarians, and the contribution of known major factors associated with cHMW adiponectin levels, including BMI and HDLC, varies with age, suggesting that its physiological significance also varies with age in the oldest old.

    Funding: This study was supported by grants from the Ministry of Health, Welfare, and Labour for the Scientific Research Projects for Longevity; a Grant-in-Aid for Scientific Research (No 21590775, 24590898, 15KT0009, 18H03055, 20K20409, 20K07792, 23H03337) from the Japan Society for the Promotion of Science; Keio University Global Research Institute (KGRI), Kanagawa Institute of Industrial Science and Technology (KISTEC), Japan Science and Technology Agency (JST) Research Complex Program 'Tonomachi Research Complex' Wellbeing Research Campus: Creating new values through technological and social innovation (JP15667051), the Program for an Integrated Database of Clinical and Genomic Information from the Japan Agency for Medical Research and Development (No. 16kk0205009h001, 17jm0210051h0001, 19dk0207045h0001); the medical-welfare-food-agriculture collaborative consortium project from the Japan Ministry of Agriculture, Forestry, and Fisheries; and the Biobank Japan Program from the Ministry of Education, Culture, Sports, and Technology.

    1. Epidemiology and Global Health
    Charumathi Sabanayagam, Feng He ... Ching Yu Cheng
    Research Article Updated


    Machine learning (ML) techniques improve disease prediction by identifying the most relevant features in multidimensional data. We compared the accuracy of ML algorithms for predicting incident diabetic kidney disease (DKD).


    We utilized longitudinal data from 1365 Chinese, Malay, and Indian participants aged 40–80 y with diabetes but free of DKD who participated in the baseline and 6-year follow-up visit of the Singapore Epidemiology of Eye Diseases Study (2004–2017). Incident DKD (11.9%) was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 with at least 25% decrease in eGFR at follow-up from baseline. A total of 339 features, including participant characteristics, retinal imaging, and genetic and blood metabolites, were used as predictors. Performances of several ML models were compared to each other and to logistic regression (LR) model based on established features of DKD (age, sex, ethnicity, duration of diabetes, systolic blood pressure, HbA1c, and body mass index) using area under the receiver operating characteristic curve (AUC).


    ML model Elastic Net (EN) had the best AUC (95% CI) of 0.851 (0.847–0.856), which was 7.0% relatively higher than by LR 0.795 (0.790–0.801). Sensitivity and specificity of EN were 88.2 and 65.9% vs. 73.0 and 72.8% by LR. The top 15 predictors included age, ethnicity, antidiabetic medication, hypertension, diabetic retinopathy, systolic blood pressure, HbA1c, eGFR, and metabolites related to lipids, lipoproteins, fatty acids, and ketone bodies.


    Our results showed that ML, together with feature selection, improves prediction accuracy of DKD risk in an asymptomatic stable population and identifies novel risk factors, including metabolites.


    This study was supported by the National Medical Research Council, NMRC/OFLCG/001/2017 and NMRC/HCSAINV/MOH-001019-00. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.