Advertisement

Long-term survival, prevalence, and cure of cancer: a population-based estimation for 818 902 Italian patients and 26 cancer types

      ABSTRACT

      Background

      Persons living after a cancer diagnosis represent 4% of the whole population in high-income countries. The aim of the study was to provide estimates of indicators of long-term survival and cure for 26 cancer types, presently lacking.

      Patients and methods

      Data on 818 902 Italian cancer patients diagnosed at age 15–74 years in 1985–2005 were included. Proportions of patients with the same death rates of the general population (cure fractions) and those of prevalent patients who were not at risk of dying as a result of cancer (cure prevalence) were calculated, using validated mixture cure models, by cancer type, sex, and age group. We also estimated complete prevalence, conditional relative survival (CRS), time to reach 5- and 10-year CRS >95%, and proportion of patients living longer than those thresholds.

      Results

      The cure fractions ranged from >90% for patients aged <45 years with thyroid and testis cancers to <10% for liver and pancreatic cancers of all ages. Five- or 10-year CRS >95% were both reached in <10 years by patients with cancers of the stomach, colon–rectum, pancreas, corpus and cervix uteri, brain, and Hodgkin lymphoma. For breast cancer patients, 5- and 10-year CRSs reached >95% after 19 and 25 years, respectively, and in 15 and 18 years for prostate cancer patients. Five-year CRS remained <95% for >25 years after cancer diagnosis in patients with liver and larynx cancers, non-Hodgkin lymphoma, myeloma, and leukaemia. Overall, the cure prevalence was 67% for men and 77% for women. Therefore, 21% of male and 31% of female patients had already reached 5-year CRS >95%, whereas 18% and 25% had reached 10-year CRS >95%.

      Conclusions

      A quarter of Italian cancer patients can be considered cured. This observation has a high potential impact on health planning, clinical practice, and patients' perspective.

      Keywords

      introduction

      In the first decade of the 2000s, persons living after a cancer diagnosis represented 4% of the whole population in high-income countries [
      • AIRTUM Working Group
      Italian cancer figures, report 2010. Cancer prevalence in Italy: Patients living with cancer, long-term survivors and cured patients.
      ,
      • Parry C.
      • Kent E.E.
      • Mariotto A.B.
      • et al.
      Cancer survivors: a booming population.
      ,
      • Gatta G.
      • Mallone S.
      • van der Zwan J.M.
      • et al.
      Cancer prevalence estimates in Europe at the beginning of 2000.
      ], and >60% of cancer patients survived longer than 5 years after diagnosis [
      • AIRTUM Working Group
      Italian cancer figures, report 2010. Cancer prevalence in Italy: Patients living with cancer, long-term survivors and cured patients.
      ,
      • Parry C.
      • Kent E.E.
      • Mariotto A.B.
      • et al.
      Cancer survivors: a booming population.
      ].
      Standard survival indicators, namely 5- or 10-year relative survival (RS) [
      • Coleman M.
      • Quaresima M.
      • Berrino F.
      • et al.
      Cancer Survival in five continents: a worldwide population-based study (CONCORD).
      ,
      • De Angelis R.
      • Sant M.
      • Coleman M.P.
      • et al.
      Cancer survival in Europe 1999–2007 by country and age: results of EUROCARE-5—a population-based study.
      ], do not differentiate patients who, in the long-term, will die because of cancer from those who will be cured and will die of other causes [
      • Francisci S.
      • Capocaccia R.
      • Grande E.
      • et al.
      The cure of cancer: a European perspective.
      ]. In cancer patients, the risk of death for specific neoplasm is highest in the initial years after diagnosis, and decreases thereafter until a time period when it becomes negligible, and all the surviving patients reach the same life expectancy of the sex- and age-matched general population [
      • Baade P.D.
      • Youlden D.R.
      • Chambers S.K.
      When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
      ,
      • Ellison L.F.
      • Bryant H.
      • Lockwood G.
      • Shack L.
      Conditional survival analyses across cancer sites.
      ].
      The general aim of the present study was to expand the spectrum of indicators of long-term survival and cure among cancer patients, in order to provide helpful information for epidemiologists and health-care planners, as well as for oncologists [
      • McCabe M.S.
      • Bhatia S.
      • Oeffinger K.C.
      • et al.
      American society of Clinical Oncology Statement: achieving high-quality cancer survivorship care.
      ] and patients [
      • Baade P.D.
      • Youlden D.R.
      • Chambers S.K.
      When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
      ]. Specific aims of this study were to compute: (i) the proportion of cancer cases expected to have the same death rates of the general population (cure fraction); (ii) the number of years after cancer diagnosis necessary to eliminate excess mortality due to cancer (time to cure); (iii) the overall proportion of cancer patients not at risk of dying as a result of cancer (cure prevalence); and (iv) the proportion of prevalent cancer patients who survived longer than ‘time to cure’ and who already reached the same death rates of the general population.

      materials and methods

      Data collected from 818 902 cancer patients diagnosed at age 15–74 years in 1985–2005 by Italian cancer registries included 454 527 cancer cases diagnosed in men (85 053 lung, 63 047 prostate, and 56 635 colorectal cancers, supplementary Table S1, available at Annals of Oncology online). Corresponding numbers in women were 364 375, including 128 004 breast, 41 864 colorectal, and 20 398 endometrial cancers (supplementary Table S1, available at Annals of Oncology online).
      Detailed description of statistical methods is provided in supplementary data, available at Annals of Oncology online: extended description of statistical methods. Briefly, the observed RS was calculated for cases diagnosed in 1985–2002 and followed up until 2007, by cancer type, sex, age at diagnosis, and period of diagnosis. RS were also modelled by means of mixture cure models, including continuous age and period of diagnosis effects [
      • AIRTUM Working Group
      Italian cancer figures, report 2010. Cancer prevalence in Italy: Patients living with cancer, long-term survivors and cured patients.
      ,
      • De Angelis R.
      • Capocaccia R.
      • Hakulinen T.
      • et al.
      Mixture models for cancer survival analysis: application to population-based data with covariates.
      ,
      • Merrill R.M.
      • Capocaccia R.
      • Feuer E.J.
      • Mariotto A.
      Cancer prevalence estimates based on tumour registry data in the Surveillance, Epidemiology, and End Results (SEER) Program.
      ]. Sex-specific model-based survival estimates were also calculated for the overall population (15–74 years), at the average age at diagnosis for each cancer type.
      Proportions of patients with the same death rates of the general population (cure fractions, supplementary Figure S1A, available at Annals of Oncology online) were calculated. In addition, we estimated complete prevalence adjusting the observed prevalence in each registry with the completeness index method [
      • AIRTUM Working Group
      Italian cancer figures, report 2010. Cancer prevalence in Italy: Patients living with cancer, long-term survivors and cured patients.
      ,
      • Merrill R.M.
      • Capocaccia R.
      • Feuer E.J.
      • Mariotto A.
      Cancer prevalence estimates based on tumour registry data in the Surveillance, Epidemiology, and End Results (SEER) Program.
      ,
      • Capocaccia R.
      • De Angelis R.
      Estimating the completeness of prevalence based on cancer registry data.
      ], conditional relative survival (CRS), time to reach 5- and 10-year CRS >95% [
      • Janssen-Heijnen M.L.G.
      • Gondos A.
      • Bray F.
      • et al.
      Clinical relevance of conditional survival of cancer patients in Europe: age-specific analyses of 13 cancers.
      ] (supplementary Figure S1B, available at Annals of Oncology online), and proportion of patients living longer than those thresholds (supplementary Figure S1C, available at Annals of Oncology online). Finally, we calculated the proportion of prevalent patients who were not at risk of dying as a result of cancer (cure prevalence, supplementary Figure S1C, available at Annals of Oncology online) [
      • Gatta G.
      • Capocaccia R.
      • Berrino F.
      • et al.
      Colon cancer prevalence and estimation of differing care needs of colon cancer patients.
      ].

      results

      Among Italian cancer patients diagnosed at aged 15–74 between 1985 and 2005, the cure fraction was highest in patients <45 years of age for thyroid (99% in women and 95% in men), testis (94%), and corpus uteri (91%). Conversely, cure fractions <10% emerged, for all ages and sexes, for liver and pancreatic cancer patients and, for patients aged 55 years or older, diagnosed with cancers of the lung, gallbladder, brain, and leukaemias (Table 1). Cure fractions were largely higher (by 10% or more) in women than in men for all age groups in patients with cancer of the oral cavity, skin melanoma, kidney, bladder, and thyroid cancers. A less clear advantage (0%–10%) for women emerged for patients with stomach and colorectal cancer, whereas for all other cancer types no difference in cure fraction emerged across age groups (Table 1).
      Table 1Estimated cure fraction by cancer type, sex, and age at diagnosis.
      Age 15–74 years.
      Italy 1985–2005
      Cancer type, ICD10Cure fraction (%)
      Men, age (years)Women, age (years)
      15–4445–5455–6465–7415–4445–5455–6465–74
      Oral cavity, C01–144227191360453729
      Oesophagus, C151696410988
      Stomach, C164431251942353128
      Colon and rectum, C18–215450484557535149
      Liver, C22732112642
      Gallbladder, C23–242615117181297
      Pancreas, C25643217742
      Larynx, C324939342949393429
      Lung, C33–341711863016117
      Skin melanoma, C437767615485787368
      Connective tissue, C47, C496754473960524743
      Breast, C5040605456
      Vagina and vulva, C51–5275605141
      Cervix uteri, C5377645646
      Corpus uteri, C5491837666
      Ovary, C5662402817
      Prostate, C6147495050
      Testis, C6294908683
      Kidney, C64–66, C686551433575625546
      Bladder, C67, D09.0, D30.3, D41.48163503589756348
      Brain, C70–72351252411572
      Thyroid, C739575604399948465
      Hodgkin lymphoma, C818063383579745033
      Non-Hodgkin lymphoma, C82–85, C964535302656403122
      Multiple myeloma, C88–90201112113523912
      Leukaemia, C91–95181297181297
      a Age 15–74 years.
      The cure prevalence proportions were particularly high for patients with cancer of testis (98%), thyroid (91% in men and 97% in women), cervix uteri (95%), corpus uteri (93%), and Hodgkin lymphoma (92%, both sexes) (Figure 1). The cure prevalence proportions were 72% for breast cancer patients, 64% for prostate, 83% in men, and 87% in women diagnosed with colorectal cancer, whereas it was less than one-third for patients with liver cancer, myeloma, and leukaemia (Figure 1). The overall cure prevalence proportion for all examined cancer types encompassed 73% (i.e. 67% of men and 77% women) of persons living after cancer diagnosis.
      Figure 1
      Figure 1Overall prevalence and cure prevalence (proportion of cancer patients who will not die of their disease), overall and by year since diagnosis, sex, and cancer type. Italy 1985–2005. At 1 January 2006, in patients aged 15–74 years living after a cancer diagnosis, calculated as a sum of age-specific estimates.
      Figure 1
      Figure 1Overall prevalence and cure prevalence (proportion of cancer patients who will not die of their disease), overall and by year since diagnosis, sex, and cancer type. Italy 1985–2005. At 1 January 2006, in patients aged 15–74 years living after a cancer diagnosis, calculated as a sum of age-specific estimates.
      In both sexes, time to cure was reached in <10 years, consistently so for different definitions used, by patients with cancers of the stomach and colon–rectum (both 5–9 years), pancreas (5–6 years), cervix and corpus uteri (5–9 years), and brain (7–8 years). In particular, time to cure was reached in <5 years by women with thyroid cancer and by men with testicular cancer (Table 2). For patients with liver and larynx cancers, non-Hodgkin lymphoma, myeloma, and leukaemia, time to cure was not reached or it was >15 years for all definitions used. For these cancers, CRS remained <90%, in comparison with the general population, and for 15 years or more after cancer diagnosis (Table 2).
      Table 2Estimates of time to cure according to different thresholds for 5- and 10-year conditional relative survival (CRS)
      Estimates are based on the relative survival function for each type and sex parameterized using mixture cure models. ‘One’ year is reported when time to reach thresholds is <1 year; ‘>25’ when threshold is not reached within 25 years.
      by cancer type, sex, and age. Italy 1985–2005
      Cancer type, ICD10Age at diagnosis
      Estimates are shown by age groups when overall annual incidence rates >10/100 000.
      (years)
      MenWomen
      Years to 5-year CRSYears to 10-year CRSYears to 5-year CRSYears to 10-year CRS
      >90%>95%>95%>90%>95%>95%
      Oral cavity, C01–1415–4479106910
      45–549111181112
      55–649111291213
      65–74101212101213
      15–749111291112
      Oesophagus, C1515–74899788
      Stomach, C1615–44577577
      45–54688577
      55–64689578
      65–74799688
      15–74689678
      Colon and rectum, C18–2115–44578577
      45–54588577
      55–64688578
      65–74689578
      15–74689578
      Liver, C2215–74151820141819
      Gallbladder, C23–2415–748910799
      Pancreas, C2515–74566566
      Larynx, C3215–44922>25
      45–5414>25>25
      55–6416>25>25
      65–7419>25>25
      15–7417>25>2517>25>25
      Lung, C33–3415–44799688
      45–54799789
      55–648910799
      65–74810108910
      15–748910799
      Skin melanoma, C4315–44366157
      45–54578379
      55–646894910
      65–7469961011
      15–74588379
      Connective tissue, C47, C4915–74691061011
      Breast, C5015–4414>25>25
      45–5461724
      55–6491925
      65–7491721
      15–7491925
      Vagina and vulva, C51–5215–7481215
      Cervix uteri, C5315–44356
      45–54577
      55–64688
      65–74689
      15–74578
      Corpus uteri, C5415–44112
      45–54245
      55–64367
      65–74578
      15–74467
      Ovary, C5615–44578
      45–54799
      55–6481010
      65–7491111
      15–7481010
      Prostate, C6145–54101518
      55–64101518
      65–74101518
      15–74101518
      Testis, C6215–44111
      45–54112
      15–74111
      Kidney, C64–66, C6815–443815258
      45–54513224811
      55–64716>2551013
      65–741020>2571215
      15–74817>2551014
      Bladder, C67, D09.0,15–44118112
      D30.3, D41.445–54213>251512
      55–64722>2531119
      65–7415>25>25818>25
      15–7410>25>2551423
      Brain, C70–7215–54788788
      Thyroid, C7315–44111
      45–54111
      55–64144
      65–74355
      15–741914111
      Hodgkin lymphoma, C8115–741791611
      Non-Hodgkin lymphoma, C82–85, C9615–448152241425
      45–541018251023>25
      55–641220>2514>25>25
      65–741322>2518>25>25
      15–741120>25>25>25>25
      Multiple myeloma, C88–9055–6418222424>25>25
      65–74172021172122
      15–74172021172122
      Leukaemia, C91–9515–4425>25>2525>25>25
      45–54>25>25>25>25>25>25
      55–64>25>25>25>25>25>25
      65–74>25>25>25>25>25>25
      15–74>25>25>25>25>25>25
      Italic values stand for all (15–74) ages.
      a Estimates are based on the relative survival function for each type and sex parameterized using mixture cure models. ‘One’ year is reported when time to reach thresholds is <1 year; ‘>25’ when threshold is not reached within 25 years.
      b Estimates are shown by age groups when overall annual incidence rates >10/100 000.
      For other cancer types, the time to reach the different thresholds was heterogeneous according to the definition used. In women with breast cancer, a 5-year CRS >90% was reached before 10 years from diagnosis (14 years for patients aged 15–44), but 5-year CRS >95% in nearly 20 years and 10-year CRS >95% in 25 years or more. For patients with prostate cancer, these times to cure were reached in 10, 15, and 18 years, respectively. Thus, time to reach these thresholds were variable for patients with kidney and bladder cancers. As a consequence (Table 3), proportions of all patients living after a cancer diagnosis who reached time to cure were relatively high in both sexes, and according to different thresholds, for cervix (>70% among 167/100 000 women) and corpus uteri (>50% among 258/100 000 women), testis (>90% among 150/100 000 men), brain (>50% among 56/100 000 men and women), thyroid cancer (>75% among 255/100 000 women), and Hodgkin lymphoma (>50% among 95/100 000 men and 78/100 000 women). Less than 10% of patients with liver, laryngeal, prostate cancers, non-Hodgkin lymphoma, myeloma, and leukaemia had already reached the same or similar death rates of the general population. Among all Italian women, 1709/100 000 were alive after a breast cancer diagnosis; 41% had already reached 5-year CRS >90%, but only 6% reached 10-year CRS >95%. Similarly, heterogeneity of proportions of cured patients according to the time-to-cure definition emerged for kidney and, most notably, for bladder cancer patients (5-year CRS >90% reached by 29%, whereas 10-year CRS >95% by only 1% among 438/100 000 men). The proportion of patients who reached 5- or 10-year CRS >95% was intermediate for colorectal cancer (30% and 27% among 422/100 000 men; 40% and 36% among 352/100 000 women), stomach cancer (38% and 37% among 109/100 000 men; 58% and 49% among 73/100 000 women), and skin melanoma (49% and 41% among 184/100 000 women) (Table 3).
      Table 3Complete prevalence (CP)
      At 1 January 2006 in patients aged 15–74 years living after a cancer diagnosis, calculated as a sum of age-specific estimates of prevalence.
      and proportion (%) of patients who reached different levels of conditional relative survival (CRS)
      Estimates are based on the relative survival function for each type and sex parameterized using mixture cure models.
      by cancer type and sex. Italy 1985–2005
      Cancer type, ICD10MenWomen
      CPFive-year CRSFive-year CRSTen-year CRSCPFive-year CRSFive-year CRSTen-year CRS
      ×100 000>90%>95%>95%×100 000>90%>95%>95%
      Oral cavity, C01–149930%23%22%4943%35%32%
      Oesophagus, C151318%15%15%429%26%26%
      Stomach, C1610947%38%37%7358%49%47%
      Colon and rectum, C18–2142241%30%27%35252%40%36%
      Liver, C22461%1%1%169%8%7%
      Gallbladder, C23–241020%14%13%1226%20%20%
      Pancreas, C251718%16%16%1322%19%19%
      Larynx, C3214115%0%0%1414%0%0%
      Lung, C33–3417423%18%17%6021%17%15%
      Skin melanoma, C4314054%38%36%18476%49%41%
      Connective tissue, C47, C494267%58%55%3570%59%55%
      Breast, C50170941%12%6%
      Vagina and vulva, C51–521940%25%18%
      Cervix uteri, C5316782%75%73%
      Corpus uteri, C5425871%56%50%
      Ovary, C5613651%43%42%
      Prostate, C615924%0%0%
      Testis, C6215095%94%93%
      Kidney, C64–66, C6818139%12%2%9757%36%26%
      Bladder, C67, D09.0, D30.3, D41.443829%5%1%9858%25%10%
      Brain, C70–725758%54%53%5667%63%63%
      Thyroid, C737474%58%54%25587%78%78%
      Hodgkin lymphoma, C819585%65%59%7888%68%52%
      Non-Hodgkin lymphoma, C82–85, C9617631%14%4%15934%7%1%
      Multiple myeloma, C88–90352%1%0%292%1%0%
      Leukaemia, C91–95877%0%0%6913%0%0%
      a At 1 January 2006 in patients aged 15–74 years living after a cancer diagnosis, calculated as a sum of age-specific estimates of prevalence.
      b Estimates are based on the relative survival function for each type and sex parameterized using mixture cure models.
      Overall, 27% of all cancer patients (21% in men and 31% in women), or 0.9% of the Italian population, had reached 5-year CRS >95% and 22% (18% in men and 25% in women) 10-year RS >95%.

      discussion

      This study showed that a quarter (27%) of persons living in Italy in the first decade of the 2000s after a cancer diagnosis had reached a death rate similar to that of the general population. In addition, nearly three quarters (73%) of them will not die as a result of their cancer. All the indicators of long-term survival showed a huge heterogeneity by cancer type, age group and, less markedly, by sex.
      Present findings for breast cancer patients were in substantial agreement with many previous studies, reporting that a small (i.e. <10%) but significant excess mortality remains at least up to 15 years after diagnosis [
      • Janssen-Heijnen M.L.G.
      • Gondos A.
      • Bray F.
      • et al.
      Clinical relevance of conditional survival of cancer patients in Europe: age-specific analyses of 13 cancers.
      ,
      • Smastuen M.
      • Aagnes B.
      • Johannsen T.B.
      • et al.
      Long-term Cancer Survival: Patterns and Trends in Norway 1965–2007.
      ,
      • Janssen-Heijnen M.L.G.
      • van Steenbergen L.N.
      • Voogd A.C.
      • et al.
      Small but significant excess mortality compared with the general population for long-term survivors of breast cancer in the Netherlands.
      ]. However, approximately half of the breast cancer patients will not die as a result of their cancer [
      • Francisci S.
      • Capocaccia R.
      • Grande E.
      • et al.
      The cure of cancer: a European perspective.
      ,
      • Woods L.M.
      • Rachet B.
      • Lambert P.C.
      • et al.
      Cure’ from breast cancer among two populations of women followed for 23 years after diagnosis.
      ], reaching a negligible excess risk of death after ∼20 years since diagnosis. A similar pattern emerged for men living after a prostate cancer diagnosis [
      • Francisci S.
      • Capocaccia R.
      • Grande E.
      • et al.
      The cure of cancer: a European perspective.
      ,
      • Baade P.D.
      • Youlden D.R.
      • Chambers S.K.
      When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
      ,
      • Smastuen M.
      • Aagnes B.
      • Johannsen T.B.
      • et al.
      Long-term Cancer Survival: Patterns and Trends in Norway 1965–2007.
      ], while a more favourable long-term survival emerged for colorectal [
      • Baade P.D.
      • Youlden D.R.
      • Chambers S.K.
      When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
      ,
      • Gatta G.
      • Capocaccia R.
      • Berrino F.
      • et al.
      Colon cancer prevalence and estimation of differing care needs of colon cancer patients.
      ,
      • Smastuen M.
      • Aagnes B.
      • Johannsen T.B.
      • et al.
      Long-term Cancer Survival: Patterns and Trends in Norway 1965–2007.
      ,
      • Lambert P.C.
      • Dickman P.W.
      • Osterlund P.
      • et al.
      Temporal trends in the proportion cured for cancer of the colon and rectum: a population-based study using data from the Finnish Cancer Registry.
      ] and invasive cervical cancers [
      • Baade P.D.
      • Youlden D.R.
      • Chambers S.K.
      When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
      ,
      • Janssen-Heijnen M.L.G.
      • Gondos A.
      • Bray F.
      • et al.
      Clinical relevance of conditional survival of cancer patients in Europe: age-specific analyses of 13 cancers.
      ,
      • Andrae B.
      • Andersson T.M.L.
      • Lambert P.C.
      • et al.
      Screening and cervical cancer cure: population based cohort study.
      ] with cure fractions >50% reached in 8 years. A cure fraction <10% emerged for lung and pancreas cancer patients, and no excess risk of death remained after 9 and 6 years since diagnosis, including 15%–20% of prevalent patients [
      • Francisci S.
      • Capocaccia R.
      • Grande E.
      • et al.
      The cure of cancer: a European perspective.
      ,
      • Smastuen M.
      • Aagnes B.
      • Johannsen T.B.
      • et al.
      Long-term Cancer Survival: Patterns and Trends in Norway 1965–2007.
      ,
      • Sinn M.
      • Striefler J.K.
      • Sinn B.V.
      • et al.
      Does long-term survival in patients with pancreatic cancer really exist? Results from the CONKO-001 study.
      ]. As elsewhere, the cure prevalence for patients with non-Hodgkin lymphoma, myeloma, and leukaemia was <50%, and for these patients excess mortality never became negligible [
      • Baade P.D.
      • Youlden D.R.
      • Chambers S.K.
      When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
      ,
      • Janssen-Heijnen M.L.G.
      • Gondos A.
      • Bray F.
      • et al.
      Clinical relevance of conditional survival of cancer patients in Europe: age-specific analyses of 13 cancers.
      ,
      • Smastuen M.
      • Aagnes B.
      • Johannsen T.B.
      • et al.
      Long-term Cancer Survival: Patterns and Trends in Norway 1965–2007.
      ].
      A substantial advantage in all indicators of long-term cancer survival emerged in women for some cancer types (e.g. colorectal, skin melanoma, bladder, kidney, thyroid, and non-Hodgkin lymphoma) [
      • Smastuen M.
      • Aagnes B.
      • Johannsen T.B.
      • et al.
      Long-term Cancer Survival: Patterns and Trends in Norway 1965–2007.
      ,
      • Cvancarova M.
      • Aagnes B.
      • Fosså S.D.
      • et al.
      Proportion cured models applied to 23 cancer sites in Norway.
      ], variously attributed to lower prevalence of co-morbidity, earlier stage at diagnosis, and better resistance to disease than men [
      • Micheli A.
      • Ciampichini R.
      • Oberaigner W.
      • et al.
      The advantage of women in cancer survival: an analysis of EUROCARE-4 data.
      ]. Moreover, a poorer long-term survival with increasing age was reported for almost all cancer types, possibly due to late recurrences or adverse treatment effects, secondary tumours, or increased co-morbidities [
      • Baade P.D.
      • Youlden D.R.
      • Chambers S.K.
      When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
      ,
      • Janssen-Heijnen M.L.G.
      • Gondos A.
      • Bray F.
      • et al.
      Clinical relevance of conditional survival of cancer patients in Europe: age-specific analyses of 13 cancers.
      ].

       strengths and limitations

      To the best of our knowledge, this is the first study reporting a wide spectrum of validated indicators of long-term survival and cure of cancer, including cure fraction and cure prevalence of particular interests to orient public health policies. In addition, for 26 cancer types (representing 95% and 97% of all cancer incidence in men and women, respectively), we estimated the time to reach the same death rates of the general population, which is of overwhelming importance for cancer patients and oncologists.
      Potential limitations of cure models are known and should be considered (supplementary data, available at Annals of Oncology online: extended description of statistical methods) [
      • Yu X.Q.
      • De Angelis R.
      • Andersson T.M.
      • et al.
      Estimating the proportion cured of cancer: some practical advice for users.
      ]. In general, cure models may not be appropriate for data with too short a follow-up to identify a plateau in the tail [
      • Othus M.
      • Barlogie B.
      • Leblanc M.L.
      • Crowley J.J.
      Cure models as a useful statistical tool for analyzing survival.
      ]. In this scenario, difficulties in identifying model parameters arose (cancer-specific excess mortality did not become negligible) and estimates of time to cure were either longer than the observation time (i.e. leukaemia) or rather sensible to the choice of the CRS threshold (i.e. prostate or breast cancers). However, in the present study, all the used models converged and fittings were graphically assessed (supplementary Figure S2 and Table S2, available at Annals of Oncology online).
      The accuracy of the present estimates depended also on the size of the study population and on the follow-up length, which, in turn, were the strengths of our study. Indeed, our population-based survival estimates were based on very large cohorts of patients followed up for >20 years after diagnosis in order to maximize the reliability of the survival parameter estimates.
      Histological subtype is an important prognostic factor at diagnosis for many neoplasms, particularly for non-Hodgkin lymphoma and leukaemia [
      • Andersson T.M.L.
      • Lambert P.C.
      • Derolf A.R.
      • et al.
      Temporal trends in the proportion cured among adults diagnosed with acute myeloid leukemia in Sweden 1973–2001: a population-based study.
      ]. Unfortunately, we were not able to calculate survival and prevalence estimates by histological subtypes [
      • AIRTUM Working Group
      Italian cancer figures, report 2010. Cancer prevalence in Italy: Patients living with cancer, long-term survivors and cured patients.
      ,
      • Baade P.D.
      • Youlden D.R.
      • Chambers S.K.
      When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
      ,
      • AIRTUM Working Group
      Italian cancer figures, report 2011. Survival of cancer patients in Italy.
      ]. We also lacked information on other important prognostic factors, in particular, stage and treatment. Previous reports have shown that stage has a prognostic effect, mainly during the first years after diagnosis, which lessens and can disappear for long-term survival [
      • Janssen-Heijnen M.L.G.
      • Gondos A.
      • Bray F.
      • et al.
      Clinical relevance of conditional survival of cancer patients in Europe: age-specific analyses of 13 cancers.
      ].
      New therapies, in particular biological treatments for solid tumours and lymphomas, have improved the outcome of cancer patients over time. There is a possibility that, for some neoplasms, adjuvant treatments may prolong survival, but they do not affect lethality [
      • Early Breast Cancer Trialists’ Collaborative Group (EBCTCG)
      • Davies C.
      • Godwin J.
      • et al.
      Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials.
      ]. Unfortunately, population-based studies with a long-term follow-up period could hardly allow these stratifications.
      RS could be biased when background cancer risk factors (e.g. smoke, HCV) carry a higher risk of related mortalities. This effect has been shown to be negligible for lung cancer [
      • Hinchliffe S.R.
      • Rutheford M.J.
      • Crowter M.J.
      • et al.
      Should relative survival be used with lung cancer data.
      ] and could result in downward RS estimates and in prolonged time to reach the same mortality of the general population.
      The generalization of results here presented is also questionable even if Italian RS levels were similar to those of most European countries [
      • De Angelis R.
      • Sant M.
      • Coleman M.P.
      • et al.
      Cancer survival in Europe 1999–2007 by country and age: results of EUROCARE-5—a population-based study.
      ].
      Present long-term survival and cancer cure estimates reflected the average survival time of large groups of people (i.e. a population) rather than an individual prognosis. Moreover, they must be interpreted considering that a quantitative estimation of lacking excess mortality is not always the equivalent of well-being. Parallel studies on cancer rehabilitation needs, including indicators of quality of life, are also necessary [
      • Baili P.
      • Hoekstra-Weebers J.
      • Van Hoof E.
      • et al.
      Cancer rehabilitation indicators for Europe.
      ].
      The availability of reliable and accurate estimates of long-term survival and cure for the increasing number of persons living many years since cancer diagnosis may be helpful not only to epidemiologists and health-care planners, but also to clinicians in developing guidelines to enhance and standardize the long-term follow-up of cancer survivors [
      • McCabe M.S.
      • Bhatia S.
      • Oeffinger K.C.
      • et al.
      American society of Clinical Oncology Statement: achieving high-quality cancer survivorship care.
      ,
      • De Moor J.S.
      • Mariotto A.B.
      • Parry C.
      • et al.
      Cancer survivors in the United States: prevalence across the survivorship trajectory and implication of care.
      ]. Most of all, they could be helpful to patients dealing with uncertainty about the future, making important life decisions, and supporting their rehabilitation demands.

      acknowledgements

      We thank Marilena Bongiovanni and cancer patients' associations stimulating and supporting the study. The authors also thank Maja Pohar Perme and Enzo Coviello for helpful comments, and Mrs Luigina Mei for editorial assistance.

      funding

      This work was supported by the Italian Association for Cancer Research (AIRC) (grant no. 11859 ).

      disclosure

      The authors have declared no conflicts of interest.

      appendix: Members of the AIRTUM Working group

      S. Virdone, A. Zucchetto (CRO Aviano National Cancer Institute of Aviano); A. Gigli (Institute for Research on Population and Social Sciences, National Research Council, Rome); S. Francisci (National Institute of Health, Rome); P. Baili, G. Gatta (Foundation IRCSS, National Cancer Institute of Milan); M. Castaing (Integrated Cancer Registry of Catania-Messina-Siracusa-Enna, Catania), R. Zanetti (Piedmont Cancer Registry, Torino); P. Contiero (Varese Cancer Registry, Foundation IRCSS, National Cancer Institute of Milan); E. Bidoli (Friuli Venezia Giulia Cancer Registry); M. Vercelli (Liguria Cancer Registry, Genova); M. Michiara (Parma Cancer Registry); M. Federico (Modena Cancer Registry); G. Senatore (Salerno Cancer Registry); F. Pannozzo (Latina Cancer Registry); M. Vicentini (Reggio Emilia Cancer Registry); A. Bulatko (Alto Adige/Sudtirol Cancer Registry); D. R. Pirino (Sassari Cancer Registry); M. Gentilini (Trento Cancer Registry); M. Fusco (Napoli Cancer Registry); A. Giacomin (Biella Cancer Registry); A. C. Fanetti (Sondrio Cancer Registry); R. Cusimano (Palermo Cancer Registry).

      Supplementary data

      references

        • AIRTUM Working Group
        Italian cancer figures, report 2010. Cancer prevalence in Italy: Patients living with cancer, long-term survivors and cured patients.
        Epidemiol Prev. 2010; 34 (28 August 2014, date last accessed): 1-188
        • Parry C.
        • Kent E.E.
        • Mariotto A.B.
        • et al.
        Cancer survivors: a booming population.
        Cancer Epidemiol Biomarkers Prev. 2011; 20: 1996-2005
        • Gatta G.
        • Mallone S.
        • van der Zwan J.M.
        • et al.
        Cancer prevalence estimates in Europe at the beginning of 2000.
        Ann Oncol. 2013; 24: 1660-1666
        • Coleman M.
        • Quaresima M.
        • Berrino F.
        • et al.
        Cancer Survival in five continents: a worldwide population-based study (CONCORD).
        Lancet Oncol. 2008; 9: 730-756
        • De Angelis R.
        • Sant M.
        • Coleman M.P.
        • et al.
        Cancer survival in Europe 1999–2007 by country and age: results of EUROCARE-5—a population-based study.
        Lancet Oncol. 2014; 15: 23-34
        • Francisci S.
        • Capocaccia R.
        • Grande E.
        • et al.
        The cure of cancer: a European perspective.
        Eur J Cancer. 2009; 45: 1067-1079
        • Baade P.D.
        • Youlden D.R.
        • Chambers S.K.
        When do I know I am cured? Using conditional estimates to provide better information about cancer survival prospects.
        Med J Aust. 2011; 194 (Erratum in Med J Aust 2011; 194: 376): 73-77
        • Ellison L.F.
        • Bryant H.
        • Lockwood G.
        • Shack L.
        Conditional survival analyses across cancer sites.
        Health Rep. 2011; 22: 21-25
        • McCabe M.S.
        • Bhatia S.
        • Oeffinger K.C.
        • et al.
        American society of Clinical Oncology Statement: achieving high-quality cancer survivorship care.
        J Clin Oncol. 2013; 31: 631-640
        • De Angelis R.
        • Capocaccia R.
        • Hakulinen T.
        • et al.
        Mixture models for cancer survival analysis: application to population-based data with covariates.
        Stat Med. 1999; 18: 441-454
        • Merrill R.M.
        • Capocaccia R.
        • Feuer E.J.
        • Mariotto A.
        Cancer prevalence estimates based on tumour registry data in the Surveillance, Epidemiology, and End Results (SEER) Program.
        Int J Epidemiol. 2000; 29: 197-207
        • Capocaccia R.
        • De Angelis R.
        Estimating the completeness of prevalence based on cancer registry data.
        Stat Med. 1997; 16: 425-440
        • Janssen-Heijnen M.L.G.
        • Gondos A.
        • Bray F.
        • et al.
        Clinical relevance of conditional survival of cancer patients in Europe: age-specific analyses of 13 cancers.
        J Clin Oncol. 2010; 28: 2520-2528
        • Gatta G.
        • Capocaccia R.
        • Berrino F.
        • et al.
        Colon cancer prevalence and estimation of differing care needs of colon cancer patients.
        Ann Oncol. 2004; 15: 1136-1142
        • Smastuen M.
        • Aagnes B.
        • Johannsen T.B.
        • et al.
        Long-term Cancer Survival: Patterns and Trends in Norway 1965–2007.
        Cancer Registry of Norway, Oslo2008 (28 August 2014, date last accessed)
        • Janssen-Heijnen M.L.G.
        • van Steenbergen L.N.
        • Voogd A.C.
        • et al.
        Small but significant excess mortality compared with the general population for long-term survivors of breast cancer in the Netherlands.
        Ann Oncol. 2014; 25: 64-68
        • Woods L.M.
        • Rachet B.
        • Lambert P.C.
        • et al.
        Cure’ from breast cancer among two populations of women followed for 23 years after diagnosis.
        Ann Oncol. 2009; 20: 1331-1336
        • Lambert P.C.
        • Dickman P.W.
        • Osterlund P.
        • et al.
        Temporal trends in the proportion cured for cancer of the colon and rectum: a population-based study using data from the Finnish Cancer Registry.
        Int J Cancer. 2007; 121: 2052-2059
        • Andrae B.
        • Andersson T.M.L.
        • Lambert P.C.
        • et al.
        Screening and cervical cancer cure: population based cohort study.
        Br Med J. 2012; 344: e900
        • Sinn M.
        • Striefler J.K.
        • Sinn B.V.
        • et al.
        Does long-term survival in patients with pancreatic cancer really exist? Results from the CONKO-001 study.
        J Surg Oncol. 2013; 108: 398-402
        • Cvancarova M.
        • Aagnes B.
        • Fosså S.D.
        • et al.
        Proportion cured models applied to 23 cancer sites in Norway.
        Int J Cancer. 2013; 132: 1700-1710
        • Micheli A.
        • Ciampichini R.
        • Oberaigner W.
        • et al.
        The advantage of women in cancer survival: an analysis of EUROCARE-4 data.
        Eur J Cancer. 2009; 45: 1017-1027
        • Yu X.Q.
        • De Angelis R.
        • Andersson T.M.
        • et al.
        Estimating the proportion cured of cancer: some practical advice for users.
        Cancer Epidemiol. 2013; 37: 836-842
        • Othus M.
        • Barlogie B.
        • Leblanc M.L.
        • Crowley J.J.
        Cure models as a useful statistical tool for analyzing survival.
        Clin Cancer Res. 2012; 18: 3731-3736
        • Andersson T.M.L.
        • Lambert P.C.
        • Derolf A.R.
        • et al.
        Temporal trends in the proportion cured among adults diagnosed with acute myeloid leukemia in Sweden 1973–2001: a population-based study.
        Br J Haematol. 2009; 148: 918-924
        • AIRTUM Working Group
        Italian cancer figures, report 2011. Survival of cancer patients in Italy.
        Epidemiol Prev. 2011; 35 (28 August 2014, date last accessed): 1-200
        • Early Breast Cancer Trialists’ Collaborative Group (EBCTCG)
        • Davies C.
        • Godwin J.
        • et al.
        Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials.
        Lancet. 2011; 378: 771-784
        • Hinchliffe S.R.
        • Rutheford M.J.
        • Crowter M.J.
        • et al.
        Should relative survival be used with lung cancer data.
        Br J Cancer. 2012; 106: 1584-1589
        • Baili P.
        • Hoekstra-Weebers J.
        • Van Hoof E.
        • et al.
        Cancer rehabilitation indicators for Europe.
        Eur J Cancer. 2013; 49: 1356-1364
        • De Moor J.S.
        • Mariotto A.B.
        • Parry C.
        • et al.
        Cancer survivors in the United States: prevalence across the survivorship trajectory and implication of care.
        Cancer Epidemiol Biomarkers Prev. 2013; 22: 561-570