Patients with cancer who will be cured and projections of complete prevalence in Italy from 2018 to 2030.

Introduction

Updated and detailed data on the number and characteristics of people living after a cancer diagnosis (i.e. cancer prevalence) are fundamental for healthcare planning, resource allocation, or cost estimation. 1 , 2 , 3 , 4 Cancer survivors are generally classified according to the length of survival time 1 , 5 and the outcome of the disease. 6 , 7 They have complex and heterogeneous health needs concerning medical care, psychosocial support, practical assistance, and rehabilitation. 8 , 9

A growing number of epidemiological studies have focused on quantifying the long-term impact on the healthcare system of people living after a cancer diagnosis, that is, survivors measured by complete prevalence ( Table 1 ), which cannot be directly measured by cancer registry data due to limited follow-up periods. 10 , 11

This article aimed to estimate the complete prevalence in Italy from 2018 to 2030 for the most frequent cancer types by sex, age, and time since diagnosis. In addition, the study aimed to define the residual excess risk of death of cancer survivors by computing the cure prevalence (CurePrev; i.e. the number and proportion of prevalent cases who will not die of cancer) and how this indicator changed with time since diagnosis. This information is lacking in Italy and elsewhere.

Materials and methods

A detailed description of the study population and statistical methods used has been recently published. 10 In brief, we included observed incidence data collected until 2017, with follow-up of vital status as of 31 December 2018, by 31 population-based Italian cancer registries (i.e. 47% of the Italian population, 43% of the population in North Central Italy and 55% in South Islands), with a registration ranging from 9 to 40 years, with a median of 22 years ( Supplementary Table S1 , available at https://doi.org/10.1016/j.esmoop.2024.103635 ).

The limited-duration prevalence on 1 January 2018 (i.e. the index date) was computed from incidence and follow-up data for each registry and all malignant tumours [10th revision of the International Statistical Classification of Diseases and Related Health Problems codes (ICD-10): C00-C43 and C45-C96], including urinary bladder cancers with benign, in situ, or uncertain behaviour (ICD-10: D09.0, D30.3, D41.4). Limited-duration prevalence was calculated by year since diagnosis and, for the period before the start of registration, we have estimated the unobserved fraction of prevalence using the completeness index method. 10

The number of prevalent cases in Italy was obtained as the sum of prevalence proportions (age-, sex-, and cancer type-specific, pooled from registries in the North Central and the South Islands areas included) multiplied by the corresponding Italian population in the same areas at the index date. 12 The complete prevalence was presented for all cancer types that affected at least 10 per 100 000 individuals in Italy.

The proportion of prevalent cases (by area, cancer type, sex, and age) was projected after 2018 using a linear regression model based on the last three calendar years available (i.e. 2016, 2017, and 2018; for registries with missing incidence data in 2016 or 2017, earlier years were used). 10 The assumption of a linear and constant trend of prevalence was shown to be reliable in the medium term for common cancer types. 1 , 11 The projected proportions of prevalence from registries in the North Central and the South Islands areas included in this study were multiplied by the corresponding Italian population in the same areas at the index date by sex and age ( Supplementary Table S1 , available at https://doi.org/10.1016/j.esmoop.2024.103635 ). The Italian population is observed until 2021 and forecasted for subsequent years. 12

The CurePrev is the proportion (or number) of prevalent patients who will not die of cancer, including people with the same life expectancy as the corresponding group in the general population. It was calculated for all prevalent patients and for those who already survived at least 5, 10, and 15 years. CurePrev at attained age x and follow-up time t (years since diagnosis) was estimated as of 1 January 2018, as follows:

where CF x–t is the cure fraction (i.e. the proportion of cured patients diagnosed at age x – t in 2010), Prev t ( x ) is the number of prevalent cases at t years from diagnosis, and NS x–t ( t ) is the net survival of patients diagnosed at age x–t and follow-up time t . For each cancer type and sex, the overall CurePrev was calculated by summing up estimates over all ages at prevalence and time since diagnosis, divided by the overall complete prevalence for all age groups. The remaining proportion of prevalent cases (1 − CurePrev) included those who are expected to die from cancer 10 and can be interpreted as the excess risk of death of prevalent patients.

Statistical analyses were carried out with the SEER∗Stat software (National Cancer Institute, Bethesda, MD), SAS NLIN (SAS Institute, Cary, NC), and the ComPrev software (National Cancer Institute). 10

Results

In Italy, 3 347 809 people were alive in 2018 after a cancer diagnosis, corresponding to 5.6% of the Italian population ( Supplementary Table S2 , available at https://doi.org/10.1016/j.esmoop.2024.103635 ). Of these, 1.5 million were men (5.2% of Italian men) and 1.8 million were women (6.0% of women). More than 2.2 million people (i.e. 3.7% of all Italians) have been alive for ≥5 years since diagnosis and 1.4 million (2.4% of Italians) since ≥10 years. Prevalence proportions increased with age: 0.1% of children below age 15 years (9071 or 113 per 100 000 children), 1.0% at age 15-44 years (208 854), 3.5% at 45-54 years (336 759), 6.9% at 55-64 years (550 730), 13.3% at 65-74 years (883 341), and ∼20% after age 75 years (1 359 054). The age distribution of prevalent cases in 2018 for the most frequent cancer types is shown in Supplementary Table S3 , available at https://doi.org/10.1016/j.esmoop.2024.103635 . Overall, 50% have been diagnosed with breast, prostate, and colorectal cancers ( Supplementary Table S4 , available at https://doi.org/10.1016/j.esmoop.2024.103635 ) and the percentage of prevalent cases diagnosed since ≥10 years was 50% for patients with cancer of corpus uteri, 48% for those with breast cancer, 46% for those with non-Hodgkin’s lymphoma, and 45% for those with skin melanoma ( Supplementary Table S5 , available at https://doi.org/10.1016/j.esmoop.2024.103635 ).

In 2030, 4 012 376 people are expected to live in Italy after a cancer diagnosis, corresponding to 6.9% of the population (6923 per 100 000; Table 2 ). In particular, 1 053 633 women will live after a breast cancer diagnosis (3564 per 100 000 women), 559 903 men after prostate cancer (1972 per 100 000 men), and 469 257 people after colorectal cancer diagnosis (238 751 men and 230 506 women, 841 per 100 000 men and 780 per 100 000 women). For all cancer types combined, an annual increase of 1.5% was estimated (1.6% in women and 1.3% in men) in the period 2018-2030. In terms of the proportion of prevalent cases, the increase will be more marked, 1.8% per year, given the expected decline in the Italian population. Large annual increases are foreseen for the absolute number of prevalent patients with thyroid cancer (+3.1%) and skin melanoma (+3.6%), which will be, in terms of prevalent cases, third and fifth in women (727 and 467 per 100 000, respectively). Conversely, a stable number of prevalent cases is expected for patients with ovarian cancer (180 per 100 000), leukaemia (153 per 100 000), and central nervous system cancers. A decrease is expected for prevalent patients with stomach (−1.8%), cervix uteri (−1.1%), larynx (−2.3% overall, +0.4% in women, not shown), and liver (−0.9%) cancers.

From 2018 to 2030, prevalent cases in Italy will increase by ∼665 000 ( Table 3 ), 247 000 for women living after breast cancer, 133 000 for men with prostate cancer, 97 000 after skin melanoma, and 90 000 after thyroid cancer. Prevalent cases in 2030 are estimated to be ∼7% of men and 10% of women between ages 45 and 74 years ( Supplementary Table S6 , available at https://doi.org/10.1016/j.esmoop.2024.103635 ) and 26% in men and 19% in women aged ≥75 years. More than one-half of prevalent cases in 2030 (i.e. 2 million or 3.5% of the overall population) will be diagnosed ≥10 years before ( Figure 1 and Table 3 ) and this group will increase by 42% between 2018 and 2030 explaining almost all (i.e. 90%) of the increase in prevalent cases. In particular ( Table 3 ), in the considered period, an increase of those living ≥10 years since diagnosis was expected after prostate cancer (+121%), thyroid cancer (+81%), and skin melanoma (+62%), while limited variation is expected for those diagnosed with corpus uteri (+29%), bladder (+22%), and lung (+21%) cancers.

The distribution of all prevalent cases and of those who will not die of cancer (i.e. CurePrev, in green area) by single year since diagnosis are shown in Figure 2 . CurePrev was obtained by adding up all the vertical bars (i.e. years since diagnosis) and represents 85.6% of all prevalent cases, accounting for 2 865 749 people ( Table 4 ). CurePrev became 93.0% for those who survived ≥5 years, 95.7% for those who survived ≥10 years, and 97.7% for those who survived ≥15 years, with limited differences between men and women ( Supplementary Figure S1 , available at https://doi.org/10.1016/j.esmoop.2024.103635 ). Marked variations of CurePrev emerged according to the attained age ( Supplementary Figure S2 , available at https://doi.org/10.1016/j.esmoop.2024.103635 ): 94.0% in patients <15 years of age, 92.1% at 15-44 years of age, 82.6% at 65-74 years of age, and 86.0% at ≥75 years of age (older adult groups included patients diagnosed at younger age many years earlier and now cured). Among prevalent cases alive ≥5 years since diagnosis, CurePrev became 98.6% for patients aged <15 years, 96.5% at attained age 15-44 years, 95.8% at 45-54 years, 94.0% at 55-64 years, and ∼92% at age ≥65 years.

Almost all (99.3%) patients who lived after thyroid or testicular cancer are expected to be cured ( Table 4 ), with proportions >90% for patients with skin melanoma (95.5%), Hodgkin’s lymphoma (94.8%), prostate cancer (94.1%), cervix uteri cancer (93.1%), non-Hodgkin’s lymphoma (92.0%), leukaemia (91.7%), corpus uteri (91.3%), and colorectal cancer (90.3%). For patients having cancer types with more severe prognosis, CurePrev was 55.3% for lung cancer survivors, with even lower proportions estimated for patients with cancer of the pancreas (48.6%), multiple myeloma (47.2%), and liver (28.0%). Among patients who survived ≥5 years, the excess risk of death (1 − CurePrev) was <5% for most cancer types except for patients with breast cancer (8.3%) and patients with cancers of the lung (11.1%), kidney (13.2%), bladder (15.5%), vagina/vulva (16.7%), larynx (17.8%), oral cavity (21.2%), multiple myeloma (33.4%), and liver (44.9%). At 10 years after diagnosis, an excess risk of death >5% remained only for patients with cancers of the breast (5.3%), kidney and vulva/vagina (9.9%), bladder (11.8%), larynx (12.7%), oral cavity (13.6%), multiple myeloma (21.3%), and liver (27.8%; Table 4 ).

Discussion

The vast majority (86%) of people living in Italy after a cancer diagnosis in 2018 have the same life expectancy (i.e. mortality rates) as the general population. This proportion (i.e. CurePrev) rises to 93% and 96% for those living ≥5 and ≥10 years after diagnosis, respectively.

CurePrev was previously estimated for all Italian patients aged 15-74 years (it was 73% in 2006) 13 and for those with colorectal cancer (71% in the early 1990s versus 90% in the present study). 14 CurePrev adds additional evidence related to the concept of ‘cancer cure’ and, when estimated by time since diagnosis, to ‘residual excess risk of death’ for patients with cancer. Knowing how the probability of cancer death changes with time since diagnosis can promote comprehensive rehabilitation initiatives at the national and European levels. This evidence may support actions and legislative initiatives to harmonise the regulatory framework among the European Countries to avoid discrimination (financial, but not only) 3 , 8 among citizens being cured of cancer. 15

Our present results confirm that Italy had one of the highest reported complete cancer prevalence in Europe (5.9% of the total population in 2020), 4 with proportions ranging from 4.2% in the UK–Ireland to 5.9% in Germany, 4 , 16 , 17 , 18 similar to what is reported in other high-income countries (4.4%-5.2%). 4 , 15 , 16 , 17 , 18 , 19 , 20

The expected increase in prevalent patients is also noteworthy since >4 million or 7% of Italians will live after a cancer diagnosis in 2030. However, the increase of prevalence, in the present study estimated using observed data for the late 2010s, is 1.5% per year overall, less marked than the 3% per year projected using observed data in the late 2000s and early 2010s in Italy 1 or the European pool of registries. 4 This pattern of a less pronounced increase than in the past is consistent with the slower growth in the number of incident cases in recent years in Italy (i.e. fewer smoking-related tumours in men, 21 stable screening adherence, 22 and decreasing diagnostic pressure on frequent cancer types such as prostate 23 and thyroid, 24 often overdiagnosed in the previous decade). In addition, the decrease in the Italian population should be highlighted, from 59.2 million in 2021 (the last year of the observed population) to 57.9 million in 2030. 12 However, the projected increase in prevalence through 2030 is massive, particularly for patients living ≥10 years after diagnosis. In 2018 they were 2.5% of all Italians (1.4 million), and by 2030 they will be 3.5% of Italians (2 million). The consequences for public health organisations and spending will be significant, necessitating new models of care to meet the needs of these patients, 9 , 25 many of whom can be considered cured. 26 , 27 , 28 , 29 , 30 , 31 , 32

Strengths and limitations

This study is the first to estimate the CurePrev by time since diagnosis for a large number of cancer types. The completeness and accuracy of the Italian Cancer Registries’ incidence and survival data were deemed satisfactory 10 and represent a major strength of the study, particularly for the estimation of long-term survival, cure, and prevalence. In addition, the size of the study population and the follow-up length (≥15 years for all registries used in the modelisation) also contributed to the reliability of the estimates of complete prevalence and indicators of cure. 10 Notably, we present more up-to-date data, and by including 47% of the Italian population, we can provide a greater representation of Italian patients than previous studies (coverage of 33% in previous Italian reports 1 and 20% in international comparisons 4 ). Methods of estimation of complete prevalence are validated 10 and comparable with international studies. 4

Among the limitations of the study, it should be mentioned that we are not able to categorise the complete prevalence or to use CurePrev to distinguish chronic patients, those with long-term side-effects, those with disease recurrence or progression, and those completely cured or in complete remission and health status comparable to peers never diagnosed with cancer. The most restrictive hypothesis in our models is that the same risk of death is assumed for the cured as for the general population and the excess risk is attributed to all fatal cases. The lack of standardised and widely accepted methods for estimating cancer cure indicators also suggests the need for caution in the international comparisons and interpretation of results for cancer cure indicators. 6 , 7 , 33 , 34

The coronavirus disease 2019 (COVID-19) epidemic may have an impact on projections of prevalent cases after 2020. The stable trend in cancer prevalence after 2018 was possibly altered by cancer incidence changes resulting from a reduction in routine diagnostic activities, poor outcomes due to delays in treatment, and changes in the population age structure due to high mortality among older adults, particularly in the 2020s. 4 However, complete prevalence is a rather smooth indicator over time 1 and the increased risk of death related to COVID-19 appears to be temporary for patients with cancer. 35 Only more updated data will allow us to properly quantify the impact of COVID-19 on cancer prevalence.

Conclusions

In 2030, 6.9% of the Italian population will live after a cancer diagnosis, yet 7 out of 8 (86%) have the same life expectancy as the general population. These results strongly encourage evidence-based policies aimed at improving long-term clinical follow-up, quality of life, and rehabilitation of people with cancer throughout the course of the disease. Prevalence estimates are essential to enhance data-driven, consistent cancer control planning and, as such, these data should be part of the national cancer registration.

Acknowledgements

The authors thank Mrs Ilaria Calderan for her editorial assistance.

Funding

The work leading to this manuscript was supported by the AIRC IG [grant number 28893] and by the Italian Ministry of Health (Ricerca Corrente) (no grant number). The funding sources had no involvement in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

Disclosure

The authors have declared no conflicts of interest.

Contributor Information

S. Guzzinati, Email: stefano.guzzinati@azero.veneto.it.

L. Dal Maso, Email: dalmaso@cro.it.

AIRTUM Working Group:

Emanuele Crocetti , Sandra Mallone , Daniela Pierannunzio , Paolo Contiero , Giovanna Tagliabue , Laura Memo , Gianfranco Manneschi , Alessandra Ravaioli , Francesco Cuccaro , Lorenzo Richiardi , Claudia Casella , Alessia Anna di Prima , Giovanni Maifredi , Monica Lanzoni , Claudia Cirilli , Silvia Leite , Maria Michiara , Serena Ferraioli , Maurizio Zarcone , Maria Francesca Vitale , Erica Giacomazzi , Silvia Ghisleni , Isabella Bisceglia , Maria A. Gentilini , Fabio Vittadello , Eugenia Spata , Stefano Marguati , Luciana Del Riccio , Elisa Concas , Alessandra Sessa , Antonino Ziino Colanino , Rita Prazzoli , Gianfabrizio Ferrari , and Luisa Canu

Supplementary data

Supplementary Material

References

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Associated Data

Supplementary Materials

Supplementary Material