The impact of the COVID-19 pandemic on Italian population-based cancer screening activities and test coverage: Results from national cross-sectional repeated surveys in 2020
- Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Italy
- Azienda Unità Sanitaria Locale Di Modena, Italy
- Istituto per lo Studio, la Prevenzione e la Rete Oncologica (ISPRO), Italy
- Registro Tumori del Veneto, Azienda Zero, Italy
- Centro di Prevenzione Oncologica, Azienda Ospedaliero-Universitaria Città della Salute e della Scienza di Torino, Italy
- Servizio Prevenzione Collettiva e Sanità Pubblica, Direzione Generale Cura della Persona, Salute e Welfare, Regione Emilia-Romagna, Italy
- Istituto Superiore di Sanita, Italy
- Osservatorio Nazionale Screening, Italy
Abstract
Background:
In Italy, regions have the mandate to implement population-based screening programs for breast, cervical, and colorectal cancer. From March to May 2020, a severe lockdown was imposed due to the COVID-19 pandemic by the Italian Ministry of Health, with the suspension of screening programs. This paper describes the impact of the pandemic on Italian screening activities and test coverage in 2020 overall and by socioeconomic characteristics.
Methods:
The regional number of subjects invited and of screening tests performed in 2020 were compared with those in 2019. Invitation and examination coverage were also calculated. PASSI surveillance system, through telephone interviews, collects information about screening test uptake by test provider (public screening and private opportunistic). Test coverage and test uptake in the last year were computed by educational attainment, perceived economic difficulties, and citizenship.
Results:
A reduction of subjects invited and tests performed, with differences between periods and geographical macro areas, was observed in 2020 vs. 2019. The reduction in examination coverage was larger than that in invitation coverage for all screening programs. From the second half of 2020, the trend for test coverage showed a decrease in all the macro areas for all the screening programs. Compared with the pre-pandemic period, there was a greater difference according to the level of education in the odds of having had a test last year vs. never having been screened or not being up to date with screening tests.
Conclusions:
The lockdown and the ongoing COVID-19 emergency caused an important delay in screening activities. This increased the preexisting individual and geographical inequalities in access. The opportunistic screening did not mitigate the impact of the pandemic.
Funding:
This study was partially supported by Italian Ministry of Health – Ricerca Corrente Annual Program 2023 and by the Emilian Region DGR 839/22.
Editor's evaluation
The authors provide important evidence for the impact of the COVID-19 pandemic on screening for breast, cervix, and colorectal cancer in Italy. They compared Invitation and examination coverage, conducted telephone interviews, and investigated screening test coverage, before and during the pandemic, according to educational attainment, perceived economic difficulties and citizenship. Their findings convincingly show that the lockdown and pandemic restrictions caused delays in screening and increased the pre-existing individual and geographical inequalities in access.
https://doi.org/10.7554/eLife.81804.sa0Introduction
Since early 2020, the COVID-19 pandemic and the measures taken by most governments to control the spread of the virus had an impact on all health services, but also on people’s behaviors and attitudes toward prevention (Kumari et al., 2021; Moynihan et al., 2021). The combination of reduced health service delivery for non-COVID-19 activities and a lower propensity to access health services by the population caused appreciable delays in cancer diagnosis in most countries where the phenomenon has been studied (Ferrara et al., 2021; Dinmohamed et al., 2020; Nyante et al., 2021).
Cancer screening tests are nonurgent services, and thus they were among the first suspended activities during the first pandemic wave in most European countries (Figueroa et al., 2021). On the other hand, organized screening programs actively invite the target population. The active invitation allows to accurately plan the workload, which represented an opportunity for organized screening programs to resume post-lockdown activities in a rational way according to accurate prioritization, aiming to minimize the impact of the pandemic on cancer diagnosis delays (Castanon et al., 2021, Campbell et al., 2021). Thus, the presence of a structured and well-organized program has been recognized as a possible element favoring the resilience of health services to the pandemic disruption (Mangone et al., 2022).
In Italy, a national law included organized screening programs for breast, cervical, and colorectal cancers among the public health interventions that all the regions must carry out (Decreto del Presidente del Consiglio dei Ministri, 12 gennaio, 2017). The target population, the test, and the intervals used are reported in Table 1. Before the COVID-19 pandemic, the invitation coverage was almost complete for all screening programs in Central Italy, and for breast cancer in Northern Italy, while for colorectal cancer screening, there were still areas, especially in Southern Italy, where large parts of the target population were not actively invited. There are large differences in participation in all three screening programs among regions, with the northern regions achieving higher participation rates than the southern ones. Routine statistics on activity and performance indicators are produced by the National Screening Monitoring Center (ONS), which is a technical network appointed by the Italian Ministry of Health to monitor regional screening campaigns, and they are available at https://www.osservatorionazionalescreening.it/.
Table 1
Italian Ministry of Health recommendations for cancer screening programs.
| Target population | Test | Interval | |
|---|---|---|---|
| Cervical cancer | Women 25–64 years | Pap test (25 to 29/34 years) HPV test (30/35–64 years) | 3 years after negative Pap 5 years after negative HPV |
| Breast cancer | To be implemented: Women 50–69 years Suggested: Women 45–49 years Women 70–74 years | Mammography | 2 years for women 50–74 1 year for women 45–49 |
| Colorectal cancer | To be implemented: Women and men 50–69 years Suggested: Women and men 70–74 years | Fecal immunochemical test (FIT) or Sigmoidoscopy at 58/60 years | 2 years after negative FIT Once in a life sigmoidoscopy |
Across the country, opportunistic screening – offered by both private and public providers – is common and does not have a specific informative flow for reporting and monitoring. In 2010–13 in Italy, test coverage in the target population that reaches 75, 80, and 48% for breast, cervical, and colorectal cancers, respectively. The contribution of opportunistic screening to coverage differed across the three screening programs with about one fourth, one third, and one sixth of the coverage attributable to opportunistic testing for breast, cervical, and colorectal cancer screening test coverage, respectively (Carrozzi et al., 2015).
In Italy, the first diagnosis of COVID-19 was made on February 20, 2020, and a strict lockdown started on March 8 (Marziano et al., 2021). The impact of this first wave in terms of deaths was very strong and concentrated in Northern Italy. A second wave started in October and lasted until the end of the year, involving all the Italian regions (Figure 1). Control measures differed in the three periods: from March to May, the lockdown stopped all nonessential activities; during the summer, almost all restrictions were removed; while during the October to December restrictions, school closures, limits to movement and recommendations to work from home were applied on a regional or even provincial basis according to incidence (Manica et al., 2021).
Figure 1
Cumulative incidence (left) and mortality (right) rates in the first (upper panel, March–June 2020) and second COVID-19 wave (lower panel, July–December 2020) per 100,000 inhabitants.
Mortality is referred to the date of incidence. Rates are computed by province, bold lines define the macro areas, North, Center, and South, and Islands. Data from the National Institute of Health, Italy, 2020.
The aim of this paper is to describe the impact of the pandemic and infection control measures on the activities of Italian screening programs in terms of invitations and screening tests performed during the first year of the pandemic and to investigate how this affected the population screening test coverage overall and by socioeconomic characteristic of the target population.
Methods
Setting and description of the infection control measures
In Italy, breast, cervical, and colorectal cancer screenings are recommended, and regional health systems are in charge of implementing them according to the recommendations of the European Commission and of the Italian Ministry of Health. The target ages, intervals, and test modalities recommended in Italy are reported in Table 1; Ministero della Salute e Osservatorio Nazionale Screening, 2006, Ronco et al., 2012.
After the first COVID-19 case was diagnosed on February 20, apparently, small clusters were identified and restrictions on movements in small areas in Northern Italy were set. On March 9, the first lockdown measures were put in place for the whole country, causing the suspension of screening first-level activities. On the contrary, national directives recommended maintaining diagnostic assessment in those who tested positive and assuring all oncological follow-up (Decreto del Presidente del Consiglio dei Ministri del 9 marzo, 2020, Ministero della Salut, 2020).
The strict lockdown, that is, the 'stay at home' period in which only essential activities were allowed, ended at the beginning of May 2020, but the restrictions were gradually removed until the beginning of June 2020, when only physical distancing and wearing face masks remained mandatory (Marziano et al., 2021). During the summer, COVID-19 incidence remained relatively low throughout the country, but in October it increased rapidly and new restrictions were introduced (Manica et al., 2021). Regions or provinces were classified as white, yellow, orange, and red according to a set of indicators measuring the quality of data reporting, the testing capacity, the incidence trend (the Rt), the adequacy of contact tracing, and the pressure on the health system (Riccardo et al., 2022). Each color code corresponded to a set of mandatory restrictions that the regional government should implement and eventually integrate with local measures. Among these measures, none was directed to reduce nonurgent health services and, in several regions, cancer screening had been included among the services, which had to be maintained. Nevertheless, in many areas, the pressure on hospitals became so strong that it became necessary to reduce nonurgent activities in order to redirect health professionals to COVID-19-related activities. Furthermore, in orange and red zones there were restrictions on moving from one municipality to another (even if these did not apply for medical checks/reasons) and restrictions on public transport. Figure 1 summarizes the COVID-19 incidence and mortality in Italy by geographical area during the first and the second waves in 2020.
Study design
This study presents the results of two national surveys. The first collected the screening activities, in terms of invitations and first-level tests performed, of the public, organized screening programs during 2020 and the first five months of 2021, compared with the same activities in performed 2019. The second survey is the PASSI’s survey (one of the two Italian National Health Interviews), which collects information on screening uptake by the target population, both in organized screening and in opportunistic screening.
From the first survey, we can assess how much the screening activities were slowed down by the pandemic and the magnitude of the backlog and consequent delay in screening the target population.
From the second survey, we measure the impact of the pandemic on test coverage in the target population, and the proportion of the target population who had a test in the last year. From this source, we can distinguish the tests performed in public programs and in private opportunistic screening, and we can also measure the coverage by socioeconomic characteristics of the target population.
Data sources
The National Screening Monitoring Center (ONS) monitors regional screening performances and trends, and a summary report is regularly published (https://www.osservatorionazionalescreening.it/content/rapporto-ons-2020). In October 2020, the ONS promoted an additional survey to monitor the impact of the pandemic on screening programs (Mantellini et al., 2020; Battisti et al., 2022).
An ad hoc qualitative and quantitative questionnaire was sent by the ONS to all regional cancer screening coordinators. The qualitative part included the description of the changes in screening activities adopted during the pandemic period, including the suspended activities (i.e., invitations, spontaneous access, second level tests, and assessments) and chances in invitation pace. The quantitative part collected, for the three screening programs, the absolute number of subjects invited and the absolute number of screening tests performed for the periods of January–May 2020, June–September 2020, October–December 2020, and January–May 2021 compared to those of the same periods over 2019.
Data were referred to the core target population, that is, the age group that all regions must implement (see Table 1).
PASSI’s survey is one of the two National Health Interviews (NHIS) active in Italy (Carrozzi et al., 2015; Petrelli et al., 2018). Through a continuous sampling of the population aged 18–69 residing in Italy, it conducts telephone interviews collecting information about health behaviors, health conditions, socioeconomic conditions, use of health services, and participation in preventive interventions (Baldissera et al., 2011). Sampling methods are described elsewhere; briefly a nationally representative sample stratified by age, sex, and local health authority is drawn. Participation in the survey is free and voluntary, individuals can refuse to be interviewed; the average response rate was 80% in the period 2017–2020. Nonparticipants are substituted from a list of subjects of the same stratum (Baldissera et al., 2014). The interviewers are specifically trained to process personal data safely and correctly. Individuals selected for the interview are informed by letter about the objectives of the investigation, its methods, and the arrangements taken to ensure the confidentiality of the collected information. After receiving the letter, they are contacted by phone; during the phone interview, the interviewer presents the information again and asks for the interviewee’s consent to conduct the interview.
In this study, the analyzed data were collected by PASSI between 2017 and 2020, including 44,874 (of which 6736 conducted in 2020) interviews of women aged 25–64 years informing on cervical cancer screening, 23,276 (of which 3501 conducted in 2020) interviews of women aged 50–69 years informing on breast cancer screening, and 40,826 (of which 6233 conducted in 2020) interviews of women and men aged 50–69 years informing on colorectal cancer screening. Lombardy region suspended the surveillance in 2016. For colorectal cancer screening, data from the Piedmont region are excluded from analyses using tests performed in the last year as the outcome because organized screening programs offer a flexosigmodoscopy once in life as the primary test.
PASSI provides information on test coverage in the target population, including both the share of tests performed within the organized screening programs and those performed outside (spontaneous screening). PASSI provides data on the differences in the execution of screening tests also with respect to socio-demographic characteristics. The exact number of interviews included in the analyses for each question is reported in Supplementary file 7.
Outcomes definition
Based on the ONS survey, we report the number of invitations sent during the investigation period and the number of screening examinations performed in the study period. Invitation (percentage of citizens who were sent an invitation to a screening during the analyzed period compared to the population to be invited in the period in order to reach all the target population in the screening interval, excluding undelivered invitations and noneligible subjects) and examination (percentage of citizens who performed the test compared to the population to be tested in the period in order to reach all the target population in the screening interval, excluding those with specific exclusion criteria) coverage relatively to 2017–2019 is also reported.
We also computed the 'standard months' of delay, that is, the number of months that would be required to catch up with the cumulated backlog if the program screened women at the same pace, as it did over the pre-COVID era. This parameter is obtained by multiplying the reduction in the number of tests performed during the study period compared to the same period in 2019 (% reduction) by the duration (number of months) of the study period.
Based on the date of the last test before the PASSI interview and the reported provider of the last test (free or paid out of pocket, proxy of organized and spontaneous screening, respectively), we computed the test coverage for each screening program: for breast cancer, we considered as being eligible the female population aged 50–69 years and those who reported having had a mammogram in the last 2 years as up to date with screening; for cervical cancer, we considered as being eligible the female population aged 25–64 years and those having had a Pap test in the last 3 years or an HPV-DNA test in the last 5 years as up to date with screening; for colorectal cancer, we considered as being eligible males and females aged 50–69 years and those reporting a fecal occult blood test (FOBT) in the last 2 years or a colonoscopy or sigmoidoscopy in the last 5 years as up to date with screening.
We also only considered the tests performed in the last year as an outcome for each screening test.
Statistical analysis
For the ONS surveys, only descriptive analyses are presented.
In PASSI, each Local Health Authority extracts a proportionate stratified sampling for the sex and age categories (18–34, 35–49, and 50–69 years) of the resident population. Therefore, data analysis at a national and macro-area level requires the application of appropriate weights accounting for age and geographic stratification to be representative of the whole population.
Trends of coverage are computed for each quarter of the study period, including interviews from January 2008 up to December 2020 for cervical and breast cancer and from January 2010 to December 2020 for colorectal cancer screening because the relevant items in the questionnaire were changed in 2010.
Using the tests performed in the last year as a dependent variable, we present Poisson regression models reporting the odds of having had a test in the last year vs. the odds of not having the test in the last year. Prevalence rate ratios with the relative 95% CI for age, gender, educational attainment (four categories: elementary school; middle school; high school; higher education), nationality (two categories: Italians or foreign nationals from high-income countries; foreign nationals from middle- or low-income countries - according to the World Bank classification [UNDP, 2007]) and economic difficulties (three categories: many economic difficulties; some economic difficulties; no economic difficulties) are obtained. Models are performed on interviews conducted in 2020 and for those conducted in the 2017–2019 period. No formal tests of hypothesis have been performed and no predefined significance threshold has been fixed in this study, 95% CI boundaries should be interpreted as continuous variables.
The statistical package Stata 16 software (StataCorp LP) was used to analyze the data.
Results
Impact on screening programs
In total, 21 regions out of 21 participated in the survey. In one region, Calabria, only data from three out of five provinces were available; the data from Basilicata refer to the whole period of the study, thus it is excluded from sub-period analyses; the colorectal cancer screening data from Umbria refer to the 50–74-year-old target population rather than 50–69.
With the first lockdown measures on March 9, 2020, all screening first-level activities should be suspended maintaining diagnostic assessment in those who tested already positive. Qualitative data from the survey show that, regardless of national directives, the suspension was heterogeneous. It was almost complete in most Northern and Central regions where screening invitations and test delivery were immediately suspended; in Lazio, the suspension was established late; while in other regions, according to the screening organization, test delivery was maintained for colorectal (Puglia, Umbria) and cervical (Valle D’Aosta) cancer campaigns. Assessment of people who had previously had a positive screening test was never stopped in any program. Most screening programs started again in May/June, but rules to reduce the risk of infection required avoiding crowding in waiting rooms and physical distancing in the clinics, thus the number of exams per hour was reduced by 30–50% in all programs. These restrictions lasted for the entire study period. Furthermore, many programs reported a reduction in the pace of invitations during the second wave of the pandemic in the autumn of 2020.
According to the quantitative survey, in 2020, the screening invitations decreased, for cervical, breast, and colorectal cancer screening in Northern and Southern Italy, compared with those of the 2017–2019 period. It is worth noting that Central Italy registered the best performances: cervical cancer screening programs were indeed able to maintain invitation coverage close to 100% and breast and colorectal cancer screening resulted in just below 90% (Figure 2).
Figure 2
Invitation and examination coverage for cervical, breast, and colorectal cancer screening in Italy, by year and geographical macro area.
The invitation coverage (right panel) is computed as the number of invitations sent during the year divided by the expected target population to be invited in 1 year. Test coverage (right panel) is computed as the number of tests performed during the year divided by the expected target population in that year. For breast and colorectal cancer, the target population is expected to be invited in 2 years, for cervical cancer the target population is expected to be invited in 3 years if the last test was a Pap test and every 5 years if the last test was an HPV test.
The reduction in invitations was large and consistent in all macro areas and all screening programs for the first (January to May 2020) and second (June to September 2020) periods. In the third one (October to December 2020), differences emerged: in Central Italy, programs tried to catch up with the backlog of invitations, while in Northern Italy the programs mostly continued with the pre-pandemic pace. In Southern Italy, the reduction in activity remained up to the first quarter of 2021, except for colorectal cancer screening (Figure 3).
Figure 3
Changes in the number of invitations sent (left panel) and screening tests (right panel) performed by screening programs in 2020–2021 compared to the same months in 2019, by period and geographic macro area.
Data from ONS survey.
Compared to 2017–2019, in 2020 the reduction in examination coverage was larger than the reduction in invitation coverage for all screenings and in all macro areas (Figure 1). In Central and Northern Italy, it was particularly strong in the first period and then decreased gradually (Figure 3), reaching pre-pandemic levels for breast and colorectal cancer screening in the first quarter of 2021, but not for cervix cancer screening in Northern Italy. In Southern Italy, the reduction in tests performed lasted until the end of 2020 and it is still strong for cervical and breast cancer screening in the first quarter of 2021 (Figure 3).
The delay accumulated until May 2021 in screening the target population differs by macro area, and it is larger for Southern Italy and smaller for Central Italy for the three programs. Even though the efforts in restarting invitations were dissimilar, the difference in delay between breast and cervical cancer was only 1.2 months. Ranges between regions within macro areas are important. In fact, in Northern and Central Italy one or more regions cumulated a negligible delay of fewer than 45 days, while some regions cumulated about 1 year of delay in all programs (Table 2).
Table 2
Cumulative reduction of tests performed in Italian screening programs and average cumulated delay in testing, with ranges between regions, by geographical macro area.
January 2020 to May 2021. Data from ONS survey.
| Cervix | Breast | Colorectal | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Macro area | Test cumulative reduction Jan 2020–May 2021 | Average delay in months | Range between regions | Test cumulative reduction Jan 2020–May 2021 | Average delay in months | Range between regions | Test cumulative reduction Jan 2020–May 2021 | Average delay in months | Range between regions | |||
| Minimum | Maximum | Minimum | Maximum | Minimum | Maximum | |||||||
| North | –409,092 | –6.4 | –12.1 | +7.5 | –438,744 | –4.5 | –10.1 | –0.9 | –800,101 | –5.9 | –14 | +2.7 |
| Center | –136,393 | –4.2 | –6.6 | –0.5 | –154,783 | –4.0 | –6.0 | –1.4 | –213,418 | –4.4 | –6.3 | –0.8 |
| South and Islands | –239,275 | –7.2 | –12.7 | –5.6 | –223,439 | –6.9 | –11.2 | –5.8 | –182,468 | –8.4 | –13.4 | -2 |
| Italy | –784,760 | –6.0 | –816,966 | –4.8 | –1,195,987 | –5.8 | ||||||
-
ONS: National Screening Monitoring Centre.
Impact on overall screening test coverage
The trend for test coverage as reported by PASSI showed a clear decrease in all the macro areas for the mammographic and colorectal screenings starting from the second half of 2020 (Figure 4). Also, for coverage with Pap tests or HPV tests, the decrease is appreciable, but the magnitude is smaller. It is also appreciable that in 2020 we had an inversion in a long-term trend, with a decrease in opportunistic screening in favor of organized screening for cervical cancer (Figure 5).
Figure 4
Trends of the proportion of the screening target population who declared to have had a test in due time, overall, and by the setting of the last test.
Data from the PASSI interviews. For breast cancer, we considered as being eligible the female population aged 50–69 years and those who reported as having had a mammogram in the last 2 years as up to date with screening; for cervical cancer, we considered as being eligible the female population aged 25–64 years and those having had a Pap test in the last 3 years or an HPV-DNA test in the last 5 years as up to date with screening; for colorectal cancer, we considered as being eligible males and females aged 50–69 years and those who reported as having had a fecal occult blood test (FOBT) in the last 2 years or a colonoscopy or sigmoidoscopy in the last 5 years as up to date with screening.
Figure 5
Trends of the proportion of the screening target population who declared to have had a test in due time, by geographical macro area.
Data from the PASSI interviews. For breast cancer, we considered as being eligible the female population aged 50–69 years and those who reported as having had a mammogram in the last 2 years as up to date with screening; for cervical cancer, we considered as being eligible the female population aged 25–64 years and those having had a Pap test in the last 3 years or an HPV-DNA test in the last 5 years as up to date with screening; for colorectal cancer, we considered as being eligible males and females aged 50–69 years and those who reported having had a fecal occult blood test (FOBT) in the last 2 years or a colonoscopy or sigmoidoscopy in the last 5 years as up to date with screening.
The decrease in test coverage is steeper in people with a lower level of educational level or with many perceived economic difficulties (Figures 6 and 7). For cervical cancer, the proportion of women aged 25–64 years that declared to have a test in the last year decreased dramatically for the screening program and to a lesser extent for opportunistic tests. For breast and colorectal cancer, the reduction was smaller and all attributable to organized screening (Figure 8).
Figure 6
Trends of the proportion of the screening target population who declared to have had a test in due time, by education.
Data from the PASSI interviews. For breast cancer, we considered as being eligible the female population aged 50–69 years and those who reported as having had a mammogram in the last 2 years as up to date with screening; for cervical cancer, we considered as being eligible the female population aged 25–64 years and those having had a Pap test in the last 3 years or an HPV-DNA test in the last 5 years as up to date with screening; for colorectal cancer, we considered as being eligible males and females aged 50–69 years and those who reported as having had a fecal occult blood test (FOBT) in the last 2 years or a colonoscopy or sigmoidoscopy in the last 5 years as up to date with screening. Educational attainment was groped in two categories: low (no title, elementary school, or middle school); high (high school or higher education).
Figure 7
Trends of the proportion of the screening target population who declared to have had a test in due time, by economic difficulties, Data from the PASSI interviews.
For breast cancer, we considered as being eligible the female population aged 50–69 years and those who reported as having had a mammogram in the last 2 years as up to date with screening; for cervical cancer, we considered as being eligible the female population aged 25–64 years and those having had a Pap test in the last 3 years or an HPV-DNA test in the last 5 years as up to date with screening; for colorectal cancer, we considered as being eligible males and females aged 50–69 years and those who reported as having had a fecal occult blood test (FOBT) in the last 2 years or a colonoscopy or sigmoidoscopy in the last 5 years as up to date with screening. Economic difficulties are classified into three categories: many economic difficulties; some economic difficulties; no economic difficulties.
Figure 8
Proportion of the target population who declared having had the screening test in the last year, by year and setting where the test was last performed.
Data from the PASSI interviews.
Multivariate Poisson models show that the probability of having a test in the last year was lower even when adjusting for all other variables (Table 3). Furthermore, stratifying the Poisson models by period, in 2020, the probability of having had a test in the last year showed larger differences according to the level of education than in the pre-pandemic period for the three screenings (Table 4); nevertheless, the differences could be due to random fluctuations. Furthermore, in 2020, for breast cancer screening only foreigners had a lower probability of having had a test than Italians, inverting what was observed in the pre-pandemic period (Table 3). The differences by age and economic difficulties remained substantially unchanged in the pandemic compared with the pre-pandemic period.
Table 3
Multivariable Poisson regression models comparing the prevalence of having had a test in the last year by age, sex, familial status, socioeconomic characteristics, citizenship, and pre-pandemic and pandemic period for cervical, breast, and colorectal cancer screening in Italy.
PRR: Prevalence Rate Ratio.
| Cervix | Breast | Colorectal | |||||||
|---|---|---|---|---|---|---|---|---|---|
| PRR | 95% CI | PRR | 95% CI | PRR | 95% CI | ||||
| Age (years) | |||||||||
| 25–34 | 1.06 | 1.01 | 1.11 | ||||||
| 35–49 | 1.10 | 1.06 | 1.14 | ||||||
| 50–64 | ref. | ||||||||
| 50–59 | 1.13 | 1.08 | 1.18 | ref. | |||||
| 60–69 | ref. | 1.15 | 1.10 | 1.20 | |||||
| Sex | |||||||||
| Male | ref. | ||||||||
| Female | 0.99 | 0.95 | 1.03 | ||||||
| Familial status | |||||||||
| Married or with partner | 1.09 | 1.05 | 1.13 | 1.03 | 0.99 | 1.08 | |||
| Alone | ref. | ref. | |||||||
| Educational level | |||||||||
| No title/elementary | ref. | ref. | ref. | ||||||
| Middle school | 1.27 | 1.14 | 1.42 | 1.14 | 1.05 | 1.24 | 1.12 | 1.03 | 1.22 |
| High school | 1.46 | 1.31 | 1.63 | 1.21 | 1.12 | 1.32 | 1.20 | 1.10 | 1.30 |
| Degree | 1.65 | 1.47 | 1.84 | 1.27 | 1.16 | 1.39 | 1.12 | 1.01 | 1.23 |
| Economic difficulties | |||||||||
| Many | ref. | ref. | ref. | ||||||
| Some | 1.05 | 0.99 | 1.12 | 1.08 | 1.00 | 1.16 | 1.27 | 1.16 | 1.38 |
| None | 1.20 | 1.12 | 1.28 | 1.27 | 1.18 | 1.37 | 1.74 | 1.59 | 1.89 |
| Citizenship | |||||||||
| Italian | |||||||||
| Foreigner | 0.95 | 0.89 | 1.01 | 0.81 | 0.73 | 0.90 | 0.99 | 0.87 | 1.12 |
| Period | |||||||||
| 2017–2019 | ref. | ref. | ref. | ||||||
| 2020 | 0.76 | 0.73 | 0.80 | 0.83 | 0.78 | 0.89 | 0.74 | 0.69 | 0.79 |
Table 4
Multivariable Poisson regression models comparing the prevalence of having had a test in the last year by age, sex, familial status, socioeconomic characteristics, and citizenship in the pandemic and pre-pandemic period for cervical, breast, and colorectal cancer screening in Italy.
| Cervix | Breast | Colorectal | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017–2019 | 2020 | 2017–2019 | 2020 | 2017–2019 | 2020 | |||||||||||||
| PRR | 95% CI | PRR | 95% CI | PRR | 95% CI | PRR | 95% CI | PRR | 95% CI | PRR | 95% CI | |||||||
| Age (years) | ||||||||||||||||||
| 25–34 | 1.05 | 1.00 | 1.10 | 1.11 | 0.96 | 1.27 | ||||||||||||
| 35–49 | 1.10 | 1.06 | 1.14 | 1.10 | 0.98 | 1.24 | ||||||||||||
| 50–64 | ref. | ref. | ||||||||||||||||
| 50–59 | 1.13 | 1.08 | 1.18 | 1.14 | 1.00 | 1.29 | ref. | ref. | ||||||||||
| 60–69 | ref. | ref. | 1.15 | 1.10 | 1.20 | 1.15 | 1.01 | 1.31 | ||||||||||
| Sex | ||||||||||||||||||
| Male | ref. | ref. | ||||||||||||||||
| Female | 0.98 | 0.94 | 1.02 | 1.01 | 0.89 | 1.15 | ||||||||||||
| Familial status | ||||||||||||||||||
| Married or with partner | 1.09 | 1.05 | 1.13 | 1.10 | 0.99 | 1.22 | 1.04 | 0.99 | 1.09 | 1.01 | 0.88 | 1.15 | ||||||
| Alone | ref. | ref. | ref. | ref. | ||||||||||||||
| Educational level | ||||||||||||||||||
| No title/elementary | ref. | ref. | ref. | ref. | ref. | ref. | ||||||||||||
| Middle school | 1.24 | 1.11 | 1.39 | 1.56 | 0.98 | 2.49 | 1.10 | 1.02 | 1.20 | 1.52 | 1.14 | 2.02 | 1.10 | 1.01 | 1.20 | 1.29 | 0.94 | 1.77 |
| High school | 1.41 | 1.26 | 1.58 | 1.89 | 1.19 | 3.00 | 1.17 | 1.08 | 1.27 | 1.62 | 1.21 | 2.17 | 1.18 | 1.08 | 1.29 | 1.37 | 1.00 | 1.89 |
| Degree | 1.58 | 1.41 | 1.77 | 2.21 | 1.38 | 3.54 | 1.23 | 1.12 | 1.36 | 1.61 | 1.18 | 2.21 | 1.06 | 0.96 | 1.17 | 1.47 | 1.04 | 2.09 |
| Economic difficulties | ||||||||||||||||||
| Many | ref. | ref. | ref. | ref. | ref. | ref. | ||||||||||||
| Some | 1.06 | 1.00 | 1.13 | 1.03 | 0.82 | 1.29 | 1.08 | 1.00 | 1.17 | 1.04 | 0.81 | 1.34 | 1.27 | 1.16 | 1.39 | 1.27 | 0.95 | 1.70 |
| None | 1.20 | 1.13 | 1.28 | 1.18 | 0.94 | 1.47 | 1.27 | 1.17 | 1.37 | 1.29 | 1.00 | 1.67 | 1.72 | 1.58 | 1.88 | 1.83 | 1.38 | 2.42 |
| Citizenship | ||||||||||||||||||
| Italian | ref. | ref. | ref. | ref. | ref. | ref. | ||||||||||||
| Foreigner | 0.93 | 0.87 | 0.99 | 1.06 | 0.88 | 1.27 | 0.83 | 0.74 | 0.92 | 0.72 | 0.52 | 1.01 | 0.93 | 0.82 | 1.05 | 1.31 | 0.94 | 1.82 |
Discussion
The interruption of screening programs during lockdown over March–May 2020, as well as the reduction in their activity in the following months, caused, on average, a delay of at least 6 months for cervical cancer, 5 months for breast cervical, and 6 months for colorectal cancer screening. There are large differences in the cumulated delay between macro areas and, within macro areas, between regions (Table 2) and local health authorities (Mangone et al., 2022; Gathani et al., 2021). The largest delays are observed in those areas where screening programs had historical problems in extending invitations to the whole target population and participation was already low before the pandemic – particularly in Southern Italy but also in some areas of Northern Italy – where cervical cancer screening was recently implemented and coverage relied largely on opportunistic screening (Petrelli et al., 2018; Giorgi Rossi et al., 2019; Giorgi Rossi et al., 2018). Northern Italy was also the most affected area by the pandemic.
It is worth noting that the decrease in screening tests performed by screening programs was larger than the decrease in invitations. Even if the surveys conducted by the National Screening Monitoring Center were not designed to measure participation, this difference in the decrease indirectly shows that participation decreased during the study period.
Stopping screening programs and their slow restart caused an appreciable decrease in test coverage in the target population of breast and colorectal cancer. This decrease is smaller, as expected, for cervical cancer screening because the longer screening intervals reduce the impact of the period of absence or reduced activity; nevertheless, a change in the direction of the trend is also appreciable for cervical cancer screening. While for colorectal screening the contribution of opportunistic screening was negligible before and during the pandemic, for breast and cervical cancer opportunistic screening did not increase the proportion of population test coverage and only a small peak of women reported having paid for a test was appreciable in the strict lockdown period of March–May 2020.
The decrease in test coverage provided by organized screening programs caused an increase in inequalities. In fact, people with a lower level of education and immigrants paid the largest lack of access to secondary prevention during the pandemic.
Other studies reported an early disruption of screening activities following the lockdown, with invitations and first-level tests being stopped, and a reduction in participation when invitations restarted (Eijkelboom et al., 2021a; Peacock et al., 2021; Ho et al., 2022; Eijkelboom et al., 2021b; Bosch et al., 2022).
The reported data show large differences across countries in the screening programs’ ability to resume their activity and in catching up with the cumulated backlog. Italy has a federal health system in which the implementation of screening programs is delegated to the regional government and practically managed by the local health authorities. This organizational model, together with historical differences in the robustness of screening programs and the population’s trust in the public health system, resulted in an extreme variability in the delay cumulated in more than 1 year of COVID-19 emergency (Giorgi Rossi et al., 2019). In fact, some areas showed the ability to recover all the backlog, while the vast majority were still cumulating further delay in the first months of 2021. These differences increased the already existing geographical inequalities across the country.
Therefore, individual inequalities are also going to increase. In fact, the difference by educational level seems to be stronger in 2020 than in previous years. Furthermore, in breast cancer screening differences disadvantaging immigrants – that were small in previous years – became larger in 2020. Even if this difference could be due to chance, it may also reflect that immigrants rely mostly on organized screening and scarcely on opportunistic screening for mammography, which is a relatively expensive test. Studies from the US also showed increased inequalities consequent to the screening program interruption, with a larger impact in the decrease of screening uptake in rural areas and for beneficiaries of public insurance or those who are not insured at all (Monsivais et al., 2022, Amram et al., 2022).
Possible impact
Many studies from Italy and other countries reported a delay in diagnoses for many cancer sites (Vanni et al., 2020, Gathani et al., 2021). In some studies, a shift to more advanced stages and different initial therapeutic approaches have been observed for breast cancer and colorectal cancers (Toss et al., 2021; Vanni et al., 2021; Vives et al., 2022; Blay et al., 2021; Longcroft-Wheaton et al., 2021). Investigating the impact on the cancer stage is out of the scope of this study. Nevertheless, computing the expected delay cumulated up to now can give an estimate of the impact on mortality and, for cervical and colorectal cancer, on incidence. In fact, several mathematical models have been adapted precisely for this scope. For breast and colorectal cancer, in England, a model assuming a 12-month suspension of screening and early diagnosis pathways and reallocating all diagnoses to symptomatic diagnosis estimated an excess of about 300 breast cancer deaths (8–10% increase) and 1500 colorectal cancer deaths (15–17%) in the next 5 years (Maringe et al., 2020). The expected health impact of the disruption may be larger for clinical than for screening services. The results of simulation models focused on the analysis of the impact of screening programs disruption are suggesting that we can expect a relative increase in breast and colorectal cancer-specific mortality ranging between 1% and 3% over the next 10–30 years, depending on the duration of the disruption and on the catch-up strategies adopted. More than half of the excess deaths are expected to occur during the first 5–10 years following disruption and the health impact might be larger for older people and disadvantaged population subgroups. For cervical cancer, it has been estimated that a delay of 6 months national screening program would lead to about 600 more cancers in England that would occur in the next screening round in the absence of catch-up strategies (Castanon et al., 2021, Castanon et al., 2022). We can expect a similar impact of screening disruption in Italy, where we observed a wide variability in the length of disruption, with a 6-month average delay in the invitations (Kregting et al., 2021; de Jonge et al., 2021; Duffy et al., 2022).
Conclusions
The lockdown and the ongoing COVID-19 emergency caused an important delay in screening activities. Catch-up of backlog was different across regions, and differences cannot be explained by the severity of the pandemic in different areas. The resilience of the screening programs seems to reflect the historical robustness of the organization with areas that were able to reach higher invitation and test coverage reacting more promptly to the COVID-19 crisis. The delay of screening programs increased the preexisting individual and geographical inequalities in access. The opportunistic screening did not mitigate the pandemic impact.
Data availability
The study reports the results of mandatory monitoring activities, that are statutary duties of the National Screening Monitoring System (ONS). Although the anonymized dataset is not yet available, ONS is working to make it available as open data on its website. In the PASSI surveillance system, personal data are processed in compliance with the GDPR 2016. Although the anonymized dataset is not yet available, the National Institute of Public Health is working to make it available on request (http://www.epicentro.iss.it/passi/PresPolicy.asp) and the excel sheets with the numbers used to plot the graphs and charts of the manuscript are available and enclosed as supplementary files.
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Decision letter
-
Eduardo L FrancoSenior and Reviewing Editor; McGill University, Canada
-
Jonine FigueroaReviewer; University of Edinburgh, United Kingdom
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James F O'MahonyReviewer; Trinity College Dublin, Ireland
Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.
Decision letter after peer review:
Thank you for submitting your article "The impact of the COVID-19 pandemic on Italian population-based cancer screening activities and test coverage: results from national cross-sectional repeated surveys" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by me in a dual role of Reviewing Editor and Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Jonine Figueroa (Reviewer #1); James F O'Mahony (Reviewer #3).
Essential revisions:
As is customary in eLife, the reviewers have discussed their critiques with one another and with the Reviewing and Senior Editor. The decision was reached by consensus. What follows below is an edited compilation of the essential and ancillary points provided by reviewers in their critiques and in their interaction post-review. Please submit a revised version that addresses these concerns directly. Although we expect that you will address these comments in your response letter, we also need to see the corresponding revision clearly marked in the text of the manuscript. Some of the reviewers' comments may seem to be simple queries or challenges that do not prompt revisions to the text. Please keep in mind, however, that readers may have the same perspective as the reviewers. Therefore, it is essential that you amend or expand the text to clarify the narrative accordingly.
Reviewer #1 (Recommendations for the authors):
– The presentation of Box1 describing the screening guidelines is useful--should this be a table?
– The authors describe some of the differences between regions, it might be helpful to have a map figure describing the different regional boards and their differences in Covid rates/lockdowns during the study period or perhaps a timeline of the different mitigation measures. Not clear what the 21 regions are and confusing when subsequently state that for Calabria 2/5 missing--I am assuming there's a lower subset beyond region?
– The figures quality are poor and were hard for me to read although I could determine the information being presented. Also for Figure 1 it was unclear to me how is it that coverage is over 100% in the central region, presumably this is because of the catch up program but perhaps the timing of this needs to be separated as opposed to showing it in one bar? Why was it that Central region was able to catch up compared to other regions? Is there lessons to be learned here?
Reviewer #3 (Recommendations for the authors):
I enjoyed reading this well-written analysis. Generally the standard of academic writing in this manuscript is very high. I see some scope for adjustment to more natural English is some cases.
L27
Stating that screening is mandatory implies the population is required to screen whereas the requirement is presumably on the local health system to offer screening to all those who wish to receive it. Some change in language might be necessary.
L29
I believe COVID-19 should be capitalised.
L34-35
Sentence requires revision for clarity.
L37
among -> between
L39/40
"programmes" might be more natural than "campaigns". A programme is an ongoing service while a campaign is associated with a short term push to improve participation.
L53
I would state that the COVID pandemic emerged in early 2020 as readers in the future might benefit from this context.
L58-64
The thematic flow of this paragraph isn't quite clear. All of the individual elements are certainly relevant, but how they fit together is not.
L70
participation to -> participation in
L77-79
I would not mix fractions and percentages in one sentence.
L97
Clarify you mean the first COVID case (ie not cancer). I know this should be clear from the context but I think it is important to be specific.
L97-123
This is a very long paragraph. I suggest breaking into three.
Also, this material is more or less a description of events not a description of research methods. There is no problem with the material itself, but I think it should be placed into the introduction described as background context or similar.
L105
If follow-up was never stopped nationally (ie all regions), please state explicitly.
L110
Do you have a source to cite for the reduction by 30-50%? If there is no source can you indicate that this information might be less formal.
L125
yy-> yrs for ages, yy -> yl for yearly.
L144
PASSI -> The PASSI / PASSI's survey
Figure 1 is a good illustration of the data and easy to interpret. Would it be better to place Figures 1 and 3 and 2 and 4 side by side and using the same vertical scale allowing the reader to easily compare the trends in invitations and coverage?
All Figures are of poor resolution. I understand this may be due to the journal's submission portal rather than the file supplied by the authors but it would look better if produced at a greater resolution.
I suggest "Nationwide" or "National Average" instead of "Italy" as a geographical category. In Figures 2/4 I would place the macro region below the bar plot rather than over it.
Colonrectum -> Colorectal
Table 1, use consistent one decimal place.
In the Figure titles for Figures 1-5 I think it would be good to make clear early in the title if the data source is ONS or PASSI to help readers interpret if this is programme data or self-report of individuals from surveys. For example, the title in Figure 5 only clarifies that this is PASSI data in the last sentence of the title.
The colours in Figure 5 are not very different for Breast and Cervix. The colours chosen for colorectal are easier to tell apart. Consider how these figures will look if printed in black and white.
I would use the same 0-100% vertical scale for all three plots in Figure 5 to make the absolute difference between them clear.
The figure title for Figure 7 needs to correspond more closely with the high/low label used in the legend to make it clear what this refers to.
Similarly, for Figure 8 the groups described in the title do not clearly correspond to what is described in the legend.
Table 2
Economic difficulties: no-> none
I think some greater interpretation of Table 2 would be beneficial for the reader within the Results section.
L382
Can we state anything meaningful about the screening for foreigners in cervix and colorectal if the CIs cross one?
https://doi.org/10.7554/eLife.81804.sa1Author response
Reviewer #1 (Recommendations for the authors):
– The presentation of Box1 describing the screening guidelines is useful--should this be a table?
We changed the title in table 1.
– The authors describe some of the differences between regions, it might be helpful to have a map figure describing the different regional boards and their differences in Covid rates/lockdowns during the study period or perhaps a timeline of the different mitigation measures. Not clear what the 21 regions are and confusing when subsequently state that for Calabria 2/5 missing--I am assuming there's a lower subset beyond region?
We added a figure reporting the maps of incidence and mortality, during the first and second pandemic waves, by province and showing how the country is divided into three macro areas. We added a sentence to explain how screening activities data are collected, this should make clear that, in some regions, the screening program is only one and collects regional data, while in other regions the programs are organized at the local health authority level and data are collected separately for each program.
– The figures quality are poor and were hard for me to read although I could determine the information being presented. Also for Figure 1 it was unclear to me how is it that coverage is over 100% in the central region, presumably this is because of the catch up program but perhaps the timing of this needs to be separated as opposed to showing it in one bar? Why was it that Central region was able to catch up compared to other regions? Is there lessons to be learned here?
The definition of invitation coverage is “the percentage of citizens who were sent an invitation to a screening during the analyzed period, compared to the population to be invited in the period in order to reach all the target population in the screening interval, excluding non-eligible subjects”. Therefore it is possible that a program invites more than the expected target population in a certain period. This occurred also after the lockdown in order to catch up with the backlog.
It is difficult to understand why some programs were able to catch up and others are still facing delays. It was clearly not linked to the severity of the pandemic, but it is linked to the program’s ability to cover the population before Covid-19. We tried to expand on this point in the conclusions:
“The lockdown and the ongoing COVID-19 emergency caused an important delay in screening activities. Catch-up of backlog was different across regions, differences cannot be explained by the severity of the pandemic in different areas. The resilience of the screening programs seems to reflect the historical robustness of the organization with areas that were able to reach higher invitation and test coverage reacting more promptly to the COVID-19 crisis. The delay of screening programs increased the pre-existing individual and geographical inequalities in access. The opportunistic screening did not mitigate the pandemic impact.”
Reviewer #3 (Recommendations for the authors):
I enjoyed reading this well-written analysis. Generally the standard of academic writing in this manuscript is very high. I see some scope for adjustment to more natural English is some cases.
We thank the reviewer for this encouraging comment.
L27
Stating that screening is mandatory implies the population is required to screen whereas the requirement is presumably on the local health system to offer screening to all those who wish to receive it. Some change in language might be necessary.
We reworded the sentence. The reviewer is correct: the regional health systems must implement screening programs with the active invitation of the population.
L29
I believe COVID-19 should be capitalised.
Thanks, done.
L34-35
Sentence requires revision for clarity.
We rewrote the sentence as follows: “PASSI surveillance system, through telephone interviews, collects information about screening test uptake by test provider (public screening and private opportunistic). Test coverage and test uptake in the last year were computed, by educational attainment, perceived economic difficulties and citizenship.”
L37
among -> between
Thanks, done.
L39/40
"programmes" might be more natural than "campaigns". A programme is an ongoing service while a campaign is associated with a short term push to improve participation.
Thanks, these are definitely programs and not campaigns!
L53
I would state that the COVID pandemic emerged in early 2020 as readers in the future might benefit from this context.
Thanks, done.
L58-64
The thematic flow of this paragraph isn't quite clear. All of the individual elements are certainly relevant, but how they fit together is not.
We changed the sentence to explain the consequentiality of three concepts:
“Cancer screening tests are non-urgent services and thus they were among the first suspended activities during the first pandemic wave in most European countries. On the other hand, organised screening programmes actively invite the target population. The active invitation allows to accurately plan the workload, which represented an opportunity for organised screaming programmes to resume post-lockdown activities in a rational way according to accurate prioritisation, aiming to minimise the impact of the pandemic on cancer diagnosis delays. Thus, the presence of a structured and well-organised programme has been recognised as a possible element favouring the resilience of health services to the pandemic disruption.
L70
participation to -> participation in
Thanks, done.
L77-79
I would not mix fractions and percentages in one sentence.
We rewrote the paragraph splitting it into two sentences. We left the percentage and fractions because the second ones referred only to the covered population.
L97
Clarify you mean the first COVID case (ie not cancer). I know this should be clear from the context but I think it is important to be specific.
Thanks, done.
L97-123
This is a very long paragraph. I suggest breaking into three.
Also, this material is more or less a description of events not a description of research methods. There is no problem with the material itself, but I think it should be placed into the introduction described as background context or similar.
We made a separate subheading on the pandemic. This is part of the background but also a setting description. We prefer to maintain it in the methods in a separate subheading and maintain the introduction shorter in order to enunciate the objectives of the study before the detailed description of the context. We moved the description of the changes in screening program organization in the results since this information has been collected with the ad hoc survey by the ONS. The remaining paragraph is much smaller and, we hope, easier to read.
L105
If follow-up was never stopped nationally (ie all regions), please state explicitly.
It is correct that all assessment tests were never stopped or delayed (at least in theory, practically some delays occurred because of a lack of anesthetists where needed or patients not presenting or changing the appointments). About oncologic follow-up and post-treatment follow-up of pre-cancerous lesions, this was the directive, but this function is not always managed by the screening program, thus in some cases, we do not know how these visits have been managed. In this paragraph, we report the national recommendations.
L110
Do you have a source to cite for the reduction by 30-50%? If there is no source can you indicate that this information might be less formal.
The source of information is the survey itself. A short questionnaire on the changes in the program was included. We reported this in the methods and moved all the information collected through the survey.
L125
yy-> yrs for ages, yy -> yl for yearly.
Thanks, done.
L144
PASSI -> The PASSI / PASSI's survey
Thanks, done.
Figure 1 is a good illustration of the data and easy to interpret. Would it be better to place Figures 1 and 3 and 2 and 4 side by side and using the same vertical scale allowing the reader to easily compare the trends in invitations and coverage?
We thank the reviewer for this suggestion. We changed the figures accordingly.
All Figures are of poor resolution. I understand this may be due to the journal's submission portal rather than the file supplied by the authors but it would look better if produced at a greater resolution.
We improved the quality of the figures. Nevertheless, figures embedded in a word file cannot have a good resolution. For the final version, if accepted, we will give the original files.
I suggest "Nationwide" or "National Average" instead of "Italy" as a geographical category. In Figures 2/4 I would place the macro region below the bar plot rather than over it.
Thanks, done.
Colonrectum -> Colorectal
Thanks, done.
Table 1, use consistent one decimal place.
Thanks, done.
In the Figure titles for Figures 1-5 I think it would be good to make clear early in the title if the data source is ONS or PASSI to help readers interpret if this is programme data or self-report of individuals from surveys. For example, the title in Figure 5 only clarifies that this is PASSI data in the last sentence of the title.
We changed the figure legends identifying a figure title, where we report the source of information and the text of the legend.
The colours in Figure 5 are not very different for Breast and Cervix. The colours chosen for colorectal are easier to tell apart. Consider how these figures will look if printed in black and white.
Thanks, done.
I would use the same 0-100% vertical scale for all three plots in Figure 5 to make the absolute difference between them clear.
Thanks, done.
The figure title for Figure 7 needs to correspond more closely with the high/low label used in the legend to make it clear what this refers to.
Thanks, done.
Similarly, for Figure 8 the groups described in the title do not clearly correspond to what is described in the legend.
We thank the reviewer, there was a mistake, and we changed it accordingly.
Table 2
Economic difficulties: no-> none
Thanks, done.
I think some greater interpretation of Table 2 would be beneficial for the reader within the Results section.
We better explained what is reported in table 3 (former table 2).
L382
Can we state anything meaningful about the screening for foreigners in cervix and colorectal if the CIs cross one?
We agree with the reviewer, even if we did not adopt a significance threshold for accepting or refusing the null hypothesis, changes in cervical and colorectal cancers are not in the direction discussed for breast cancer. Sorry for this mistake, we changed the sentence accordingly.
https://doi.org/10.7554/eLife.81804.sa2Article and author information
Author details
Paolo Giorgi Rossi
Francesca Battisti
Funding
Ministero della Salute (Ricerca corrente 2023)
- Paolo Giorgi Rossi
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Acknowledgements
The authors are grateful to all the regional and local coordinators and interviewers of PASSI surveillance and to the regional screening coordinators, who contributed to the data collection. A special thanks goes to the PASSI group for their competence and commitment. This study was partially supported by the Italian Ministry of Health – Ricerca Corrente Annual Program 2023.
Ethics
Human subjects: Screening activity is monitored by ONS as statutary duties on regular basis, using a standard common set of quality indicators. During the Covid 19 pandemic ONS conducted this analysis as a part of the routine monitoring activity of the programmes performance, pooling anonymous individual data from each programme, based on a common standardised form. Approval from local ethics review boards is not required for monitoring programme activity. Regarding PASSI surveillance system, personal data are processed in compliance with the GDPR 2016. PASSI was approved by the Ethics Committee of the National Institute of Public Health on January 23, 2007. Interviews are transferred anonymously to a national archive via a secure internet connection. Personal Identifiers on paper or computers are subsequently locally destroyed.
Senior and Reviewing Editor
- Eduardo L Franco, McGill University, Canada
Reviewers
- Jonine Figueroa, University of Edinburgh, United Kingdom
- James F O'Mahony, Trinity College Dublin, Ireland
Publication history
- Received: July 12, 2022
- Preprint posted: August 17, 2022 (view preprint)
- Accepted: January 26, 2023
- Accepted Manuscript published: February 3, 2023 (version 1)
- Version of Record published: February 16, 2023 (version 2)
Copyright
© 2023, Giorgi Rossi et al.
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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The impact of the COVID-19 pandemic on Italian population-based cancer screening activities and test coverage: Results from national cross-sectional repeated surveys in 2020
eLife 12:e81804.
https://doi.org/10.7554/eLife.81804
Further reading
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- Epidemiology and Global Health
Background:
Whether natural selection may have attributed to the observed blood group frequency differences between populations remains debatable. The ABO system has been associated with several diseases and recently also with susceptibility to COVID-19 infection. Associative studies of the RhD system and diseases are sparser. A large disease-wide risk analysis may further elucidate the relationship between the ABO/RhD blood groups and disease incidence.
Methods:
We performed a systematic log-linear quasi-Poisson regression analysis of the ABO/RhD blood groups across 1,312 phecode diagnoses. Unlike prior studies, we determined the incidence rate ratio for each individual ABO blood group relative to all other ABO blood groups as opposed to using blood group O as the reference. Moreover, we used up to 41 years of nationwide Danish follow-up data, and a disease categorization scheme specifically developed for diagnosis-wide analysis. Further, we determined associations between the ABO/RhD blood groups and the age at the first diagnosis. Estimates were adjusted for multiple testing.
Results:
The retrospective cohort included 482,914 Danish patients (60.4% females). The incidence rate ratios (IRRs) of 101 phecodes were found statistically significant between the ABO blood groups, while the IRRs of 28 phecodes were found statistically significant for the RhD blood group. The associations included cancers and musculoskeletal-, genitourinary-, endocrinal-, infectious-, cardiovascular-, and gastrointestinal diseases.
Conclusions:
We found associations of disease-wide susceptibility differences between the blood groups of the ABO and RhD systems, including cancer of the tongue, monocytic leukemia, cervical cancer, osteoarthrosis, asthma, and HIV- and hepatitis B infection. We found marginal evidence of associations between the blood groups and the age at first diagnosis.
Funding:
Novo Nordisk Foundation and the Innovation Fund Denmark
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- Epidemiology and Global Health
- Genetics and Genomics
Background: To evaluate the utility of polygenic risk scores (PRS) in identifying high-risk individuals, different publicly available PRS for breast (n=85), prostate (n=37), colorectal (n=22) and lung cancers (n=11) were examined in a prospective study of 21,694 Chinese adults.
Methods: We constructed PRS using weights curated in the online PGS Catalog. PRS performance was evaluated by distribution, discrimination, predictive ability, and calibration. Hazard ratios (HR) and corresponding confidence intervals [CI] of the common cancers after 20 years of follow-up were estimated using Cox proportional hazard models for different levels of PRS.
Results: A total of 495 breast, 308 prostate, 332 female-colorectal, 409 male-colorectal, 181 female-lung and 381 male-lung incident cancers were identified. The area under receiver operating characteristic curve for the best performing site-specific PRS were 0.61 (PGS000873, breast), 0.70 (PGS00662, prostate), 0.65 (PGS000055, female-colorectal), 0.60 (PGS000734, male-colorectal) and 0.56 (PGS000721, female-lung), and 0.58 (PGS000070, male-lung), respectively. Compared to the middle quintile, individuals in the highest cancer-specific PRS quintile were 64% more likely to develop cancers of the breast, prostate, and colorectal. For lung cancer, the lowest cancer-specific PRS quintile was associated with 28-34% decreased risk compared to the middle quintile. In contrast, the hazard ratios observed for quintiles 4 (female-lung: 0.95 [0.61-1.47]; male-lung: 1.14 [0.82-1.57]) and 5 (female-lung: 0.95 [0.61-1.47]) were not significantly different from that for the middle quintile.
Conclusions: Site-specific PRSs can stratify the risk of developing breast, prostate, and colorectal cancers in this East Asian population. Appropriate correction factors may be required to improve calibration.
Funding This work is supported by the National Research Foundation Singapore (NRF-NRFF2017-02), PRECISION Health Research, Singapore (PRECISE) and the Agency for Science, Technology and Research (A*STAR). WP Koh was supported by National Medical Research Council, Singapore (NMRC/CSA/0055/2013). CC Khor was supported by National Research Foundation Singapore (NRF-NRFI2018-01). Rajkumar Dorajoo received a grant from the Agency for Science, Technology and Research Career Development Award (A*STAR CDA - 202D8090), and from Ministry of Health Healthy Longevity Catalyst Award (HLCA20Jan-0022). The Singapore Chinese Health Study was supported by grants from the National Medical Research Council, Singapore (NMRC/CIRG/1456/2016) and the U.S. National Institutes of Health [NIH] (R01 CA144034 and UM1 CA182876).
