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. 2023 Jun 6:13:1168325.
doi: 10.3389/fonc.2023.1168325. eCollection 2023.

Complete prevalence and indicators of cancer cure: enhanced methods and validation in Italian population-based cancer registries

Federica Toffolutti  1 , Stefano Guzzinati  2 , Angela De Paoli  2 , Silvia Francisci  3 , Roberta De Angelis  4 , Emanuele Crocetti  1 , Laura Botta  5 , Silvia Rossi  4 , Sandra Mallone  3 , Manuel Zorzi  2 , Gianfranco Manneschi  6 , Ettore Bidoli  1 , Alessandra Ravaioli  7 , Francesco Cuccaro  8 , Enrica Migliore  9 , Antonella Puppo  10 , Margherita Ferrante  11 , Cinzia Gasparotti  12 , Maria Gambino  13 , Giuliano Carrozzi  14 , Fabrizio Stracci  15 , Maria Michiara  16 , Rossella Cavallo  17 , Walter Mazzucco  18 , Mario Fusco  19 , Paola Ballotari  20 , Giuseppe Sampietro  21 , Stefano Ferretti  22 , Lucia Mangone  23 , Roberto Vito Rizzello  24 , Michael Mian  25 , Giuseppe Cascone  26 , Lorenza Boschetti  27 , Rocco Galasso  28 , Daniela Piras  29 , Maria Teresa Pesce  30 , Francesca Bella  31 , Pietro Seghini  32 , Anna Clara Fanetti  33 , Pasquala Pinna  34 , Diego Serraino  1 , Luigino Dal Maso  1 ; AIRTUM Working Group
Collaborators, Affiliations

Complete prevalence and indicators of cancer cure: enhanced methods and validation in Italian population-based cancer registries

Federica Toffolutti et al. Front Oncol. .

Abstract

Objectives: To describe the procedures to derive complete prevalence and several indicators of cancer cure from population-based cancer registries.

Materials and methods: Cancer registry data (47% of the Italian population) were used to calculate limited duration prevalence for 62 cancer types by sex and registry. The incidence and survival models, needed to calculate the completeness index (R) and complete prevalence, were evaluated by likelihood ratio tests and by visual comparison. A sensitivity analysis was conducted to explore the effect on the complete prevalence of using different R indexes. Mixture cure models were used to estimate net survival (NS); life expectancy of fatal (LEF) cases; cure fraction (CF); time to cure (TTC); cure prevalence, prevalent patients who were not at risk of dying as a result of cancer; and already cured patients, those living longer than TTC at a specific point in time. CF was also compared with long-term NS since, for patients diagnosed after a certain age, CF (representing asymptotical values of NS) is reached far beyond the patient's life expectancy.

Results: For the most frequent cancer types, the Weibull survival model stratified by sex and age showed a very good fit with observed survival. For men diagnosed with any cancer type at age 65-74 years, CF was 41%, while the NS was 49% until age 100 and 50% until age 90. In women, similar differences emerged for patients with any cancer type or with breast cancer. Among patients alive in 2018 with colorectal cancer at age 55-64 years, 48% were already cured (had reached their specific TTC), while the cure prevalence (lifelong probability to be cured from cancer) was 89%. Cure prevalence became 97.5% (2.5% will die because of their neoplasm) for patients alive >5 years after diagnosis.

Conclusions: This study represents an addition to the current knowledge on the topic providing a detailed description of available indicators of prevalence and cancer cure, highlighting the links among them, and illustrating their interpretation. Indicators may be relevant for patients and clinical practice; they are unambiguously defined, measurable, and reproducible in different countries where population-based cancer registries are active.

Keywords: Italy; cancer cure indicators; cure fraction; cure prevalence; prevalence; survival; time to cure.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Areas and proportions of the Italian population included in the analyses. North-Centre includes Umbria and northern CRs.
Figure 2
Figure 2
Examples of calculation of cure fraction, median life expectancy of fatal (LEF) cases (A), and time to cure (B) for Italian patients (men and women) with colorectal cancer diagnosed in 1995 at age 55–64 years. NS, model-based net survival; CNS, conditioned NS.
Figure 3
Figure 3
Calculation of cure prevalence (CurePrev) for Italian colorectal cancer patients (men and women), aged 55–64 years who were alive in 2018 (January 1st). Calculated applying to complete prevalence at attained age 55–64 the cure fraction (CF) calculated for age at diagnosis, according to years since diagnosis (Section 2.11). The red part of each bar includes cases who are expected to die because of their cancer.
Figure 4
Figure 4
Calculation of already cured (Prev>TTC) for Italian colorectal cancer patients (men and women), aged 55–64 years who were alive in 2018 (January 1st). Calculated applying to complete prevalence at attained age 55–64 the time to cure (TTC) calculated for age at diagnosis, according to years since diagnosis (Section 2.11). The red part includes patients who have not yet reached TTC.
Figure 5
Figure 5
Net survival (NS), 5-year conditional NS (5-year CNS), and corresponding model-based estimates until 24 years of follow-up for breast cancer patients (all stages) diagnosed in 1994–1996 and followed up until 2018 by age group: Age 0-44 years (A, B); 45-54 (C, D); 55-64 (E, F); 65-74 (G, H). W, Weibull; WS, Weibull, age-stratified; E, exponential; ES, exponential, age-stratified.
Figure 6
Figure 6
Cure prevalence (CurePrev) for Italian colorectal cancer patients (men and women), aged 55–64 years who were alive in 2018 (January 1st), overall and conditioned to be alive after more than 5, 10, 15, and 20 years. The red part of each bar includes cases who are expected to die because of their cancer.
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