Time-to-cure and cure proportion in solid cancers in France. A population based study

Cure indicators and prevalence by stage at diagnosis for breast and colorectal cancer patients: A population-based study in Italy

People alive many years after breast (BC) or colorectal cancer (CRC) diagnoses are increasing. This paper aimed to estimate the indicators of cancer cure and complete prevalence for Italian patients with BC and CRC by stage and age. A total of 31 Italian Cancer Registries (47% of the population) data until 2017 were included. Mixture cure models allowed estimation of net survival (NS); cure fraction (CF); time to cure (TTC, 5-year conditional NS >95%); cure prevalence (who will not die of cancer); and already cured (prevalent patients living longer than TTC). 2.6% of all Italian women (806,410) were alive in 2018 after BC and 88% will not die of BC. For those diagnosed in 2010, CF was 73%, 99% when diagnosed at stage I, 81% at stage II, and 36% at stages III-IV. For all stages combined, TTC was >10 years under 45 and over 65 years and for women with advanced stages, but ≤1 year for all BC patients at stage I. The proportion of already cured prevalent BC women was 75% (94% at stage I). Prevalent CRC cases were 422,407 (0.7% of the Italian population), 90% will not die of CRC. For CRC patients, CF was 56%, 92% at stage I, 71% at stage II, and 35% at stages III-IV. TTC was ≤10 years for all age groups and stages. Already cured were 59% of all prevalent CRC patients (93% at stage I). Cancer cure indicators by stage may contribute to appropriate follow-up in the years after diagnosis, thus avoiding patients' discrimination.

Mixture and Non-mixture Cure Models for Health Technology Assessment: What You Need to Know

There is increasing interest in the use of cure modelling to inform health technology assessment (HTA) due to the development of new treatments that appear to offer the potential for cure in some patients. However, cure models are often not included in evidence dossiers submitted to HTA agencies, and they are relatively rarely relied upon to inform decision-making. This is likely due to a lack of understanding of how cure models work, what they assume, and how reliable they are. In this tutorial we explain why and when cure models may be useful for HTA, describe the key characteristics of mixture and non-mixture cure models, and demonstrate their use in a range of scenarios, providing Stata code. We highlight key issues that must be taken into account by analysts when fitting these models and by reviewers and decision-makers when interpreting their predictions. In particular, we note that flexible parametric non-mixture cure models have not been used in HTA, but they offer advantages that make them well suited to an HTA context when a cure assumption is valid but follow-up is limited.

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

BACKGROUND

The number and projections of cancer survivors are necessary to meet the healthcare needs of patients, while data on cure prevalence, that is, the percentage of patients who will not die of cancer by time since diagnosis, are lacking.

MATERIALS AND METHODS

Data from Italian cancer registries (duration of registration ranged from 9 to 40 years, with a median of 22 years) covering 47% of the population were used to calculate the limited-duration prevalence, the complete prevalence in 2018, projections to 2030, and cure prevalence, by cancer type, sex, age, and time since diagnosis.

RESULTS

A total of 3 347 809 people were alive in Italy in 2018 after a cancer diagnosis, corresponding to 5.6% of the resident population. They will increase by 1.5% per year to 4 012 376 in 2030, corresponding to 6.9% of the resident population, 7.6% of women and ∼22% after age 75 years. In 2030, more than one-half of all prevalent cases (2 million) will have been diagnosed by ≥10 years. Those with breast (1.05 million), prostate (0.56 million), or colorectal cancers (0.47 million) will be 52% of all prevalent patients. Cure prevalence was 86% for all patients alive in 2018 (87% for patients with breast cancer and 99% for patients with thyroid or testicular cancer), increasing with time since diagnosis to 93% for patients alive after 5 years and 96% after 10 years. Among patients who survived at least 5 years, the excess risk of death (1 - cure prevalence) was <5% for patients with most cancer types except for those with cancers of the breast (8.3%), lung (11.1%), kidney (13.2%), and bladder (15.5%).

CONCLUSIONS

Study findings encourage the implementation of evidence-based policies aimed at improving long-term clinical follow-up and rehabilitation of people living after cancer diagnosis throughout the course of the disease. Updated estimates of complete prevalence are important to enhance data-driven cancer control planning.

Indicators of cure for women living after uterine and ovarian cancers: a population-based study

This study aims to estimate long-term survival, cancer prevalence, and several cure indicators for Italian women with gynaecological cancers. Thirty-one cancer registries, representing 47% of the Italian female population, were included. Mixture cure models were used to estimate Net Survival (NS), Cure Fraction, Time To Cure (5-year conditional NS>95%), Cure Prevalence (women who will not die of cancer), and Already Cured (living longer than Time to Cure). In 2018, 0.4% (121,704) of Italian women were alive after corpus uteri cancer, 0.2% (52,551) after cervical, and 0.2% (52,153) after ovarian cancer. More than 90% of patients with uterine cancers and 83% with ovarian cancer will not die from their neoplasm (Cure Prevalence). Women with gynaecological cancers have a residual excess risk of death <5% after 5 years since diagnosis. The Cure Fraction was 69% for corpus uteri, 32% for ovarian, and 58% for cervical cancer patients. Time To Cure was ≤10 years for women with gynaecological cancers aged <55 years. 74% of patients with cervical cancer, 63% with corpus uteri cancer, and 55% with ovarian cancer were Already Cured. These results will contribute to improving follow-up programs for women with gynaecological cancers and supporting efforts against discrimination of already cured ones.

Potential for Cure by Stage across the Cancer Spectrum in the United States

BACKGROUND

Cure fraction-the proportion of persons considered cured of cancer after long-term follow-up-reflects the total impact of cancer control strategies, including screening, without lead-time bias. Previous studies have not reported stage-stratified cure fraction across the spectrum of cancer types.

METHODS

Using a mixture cure model, we estimated cure fraction across stages for 21 cancer types and additional subtypes. Cause-specific survival for 2.4 million incident cancers came from 17 US Surveillance, Epidemiology, and End Results registries for adults 40 to 84 years at diagnosis in 2006 to 2015, followed through 2020.

RESULTS

Across cancer types, a substantial cure fraction was evident at early stages, followed by either a sharp drop from stages III to IV or a steady decline from stages I to IV. For example, estimated cure fractions for colorectal cancer at stages I, II, III, and IV were 62% (95% confidence interval: 59%-66%), 61% (58%-65%), 58% (57%-59%), and 7% (7%-7%), respectively. Corresponding estimates for gallbladder cancer were 50% (46%-54%), 24% (22%-27%), 22% (19%-25%), and 2% (2%-3%). Differences in 5-year cause-specific survival between early-stage and stage IV cancers were highly correlated with between-stage differences in cure fraction, indicating that survival gaps by stage are persistent and not due to lead-time bias.

CONCLUSIONS

A considerable fraction of cancer is amenable to cure at early stages, but not after metastasis.

IMPACT

These results emphasize the potential for early detection of numerous cancers, including those with no current screening modalities, to reduce cancer death.

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

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.

Surgical resection as a predictor of cancer-specific survival by stage at diagnosis and cancer type, United States, 2006-2015

BACKGROUND

When solid tumors are amenable to definitive resection, clinical outcomes are generally superior to when those tumors are inoperable. However, the population-level cancer survival benefit of eligibility for surgery by cancer stage has not yet been quantified.

METHODS

Using Surveillance, Epidemiology and End Results data allowing us to identify patients who were deemed eligible for and received surgical resection, we examined the stage-specific association of surgical resection with 12-year cancer-specific survival. The 12-year endpoint was selected to maximize follow-up time and thereby minimize the influence of lead time bias.

RESULTS

Across a variety of solid tumor types, earlier stage at diagnosis allowed for surgical intervention at a much higher rate than later-stage diagnosis. At every stage, surgical intervention was associated with a substantially higher rate of 12-year cancer-specific survival, with absolute differences of up to 51% for stage I, 51% for stage II, and 44% for stage III cancer, and stage-specific mortality relative risks of 3.6, 2.4, and 1.7, respectively.

CONCLUSIONS

Diagnosis of solid cancers in early stages often enables surgical resection, which reduces the risk of death from cancer. Receipt of surgical resection is an informative endpoint that is strongly associated with long-term cancer-specific survival at every stage.

A new cure model that corrects for increased risk of non-cancer death: analysis of reliability and robustness, and application to real-life data

BACKGROUND

Non-cancer mortality in cancer patients may be higher than overall mortality in the general population due to a combination of factors, such as long-term adverse effects of treatments, and genetic, environmental or lifestyle-related factors. If so, conventional indicators may underestimate net survival and cure fraction. Our aim was to propose and evaluate a mixture cure survival model that takes into account the increased risk of non-cancer death for cancer patients.

METHODS

We assessed the performance of a corrected mixture cure survival model derived from a conventional mixture cure model to estimate the cure fraction, the survival of uncured patients, and the increased risk of non-cancer death in two settings of net survival estimation, grouped life-table data and individual patients' data. We measured the model's performance in terms of bias, standard deviation of the estimates and coverage rate, using an extensive simulation study. This study included reliability assessments through violation of some of the model's assumptions. We also applied the models to colon cancer data from the FRANCIM network.

RESULTS

When the assumptions were satisfied, the corrected cure model provided unbiased estimates of parameters expressing the increased risk of non-cancer death, the cure fraction, and net survival in uncured patients. No major difference was found when the model was applied to individual or grouped data. The absolute bias was < 1% for all parameters, while coverage ranged from 89 to 97%. When some of the assumptions were violated, parameter estimates appeared more robust when obtained from grouped than from individual data. As expected, the uncorrected cure model performed poorly and underestimated net survival and cure fractions in the simulation study. When applied to colon cancer real-life data, cure fractions estimated using the proposed model were higher than those in the conventional model, e.g. 5% higher in males at age 60 (57% vs. 52%).

CONCLUSIONS

The present analysis supports the use of the corrected mixture cure model, with the inclusion of increased risk of non-cancer death for cancer patients to provide better estimates of indicators based on cancer survival. These are important to public health decision-making; they improve patients' awareness and facilitate their return to normal life.

Measuring population-level cure patterns for cancer patients in the United States

While the life expectancy of cancer survivors has substantially improved over time in the United States, the extent to which cancer patients are cured is not known. Population-level cure patterns are important indicators to quantify cancer survivorships. This population-based cohort study included 8978,721 cancer patients registered in the Surveillance, Epidemiology and End Results (SEER) databases between 1975 and 2018. The primary outcome was cure fractions. Five-year cure probability, time to cure and median survival time of uncured cases were also assessed. All four measures were calculated using flexible parametric models, according to 46 cancer sites, three summary stages, individual age and calendar year at diagnosis. In 2018, cure fractions ranged from 2.7% for distant liver cancer to 100.0% for localized/regional prostate cancer. Localized cancer had the highest cure fraction, followed by regional cancer and distant cancer. Except for localized breast cancer, older patients generally had lower cure fractions. There were 38 cancer site and stage combinations (31.2%) that achieved 95% of cure within 5 years. Median survival time of the uncured cases ranged from 0.3 years for distant liver cancer to 10.9 years for localized urinary bladder cancer. A total of 117 cancer site and stage combinations (93.6%) had increased cure fraction over time. A considerable proportion of cancer patients were cured at the population-level, and the cure patterns varied substantially across cancer site, stage and age at diagnosis. Increases in cure fractions over time likely reflected advances in cancer treatment and early detection.

Health status of prevalent cancer cases as measured by mortality dynamics (cancer vs. noncancer): Application to five major cancers sites

BACKGROUND

Cancer prevalence is heterogeneous because it includes individuals who are undergoing initial treatment and those who are in remission, experiencing relapse, or cured. The proposed statistical approach describes the health status of this group by estimating the probabilities of death among prevalent cases. The application concerns colorectal, lung, breast, and prostate cancers and melanoma in France in 2017.

METHODS

Excess mortality was used to estimate the probabilities of death from cancer and other causes.

RESULTS

For the studied cancers, most deaths from cancer occurred during the first 5 years after diagnosis. The probability of death from cancer decreased with increasing time since diagnosis except for breast cancer, for which it remained relatively stable. The time beyond which the probability of death from cancer became lower than that from other causes depended on age and cancer site: for colorectal cancer, it was 6 years after diagnosis for women (7 years for men) aged 75-84 and 20 years for women (18 years for men) aged 45-54 years, whereas cancer was the major cause of death for women younger than 75 years whatever the time since diagnosis for breast and for all patients younger than 75 years for lung cancer. In contrast, deaths from other causes were more frequent in all the patients older than 75 years. Apart from breast cancer in women younger than 55 years and lung cancer in women older than 55 years and men older than 65 years, the probability of death from cancer among prevalent cases fell below 1%, with varying times since diagnosis.

CONCLUSIONS

The authors' approach can be used to better describe the burden of cancer by estimating outcomes in prevalent cases.

Cancer Cure and Consequences on Survivorship Care: Position Paper from the Italian Alliance Against Cancer (ACC) Survivorship Care Working Group

A multidisciplinary panel of experts and cancer patients developed a position paper to highlight recent evidence on "cancer cure" (ie, the possibility of achieving the same life expectancy as the general population) and discuss the consequences of this concept on follow-up and rehabilitation strategies. The aim is to inform clinicians, patients, and health-care policy makers about strategies of survivorship care for cured cancer patients and consequences impacting patient lives, spurring public health authorities and research organizations to implement resources to the purpose. Two identifiable, measurable, and reproducible indicators of cancer cure are presented. Cure fraction (CF) is >60% for breast and prostate cancer patients, >50% for colorectal cancer patients, and >70% for patients with melanoma, Hodgkin lymphoma, and cancers of corpus uteri, testis (>90%), and thyroid. CF was >65% for patients diagnosed at ages 15-44 years and 30% for those aged 65-74 years. Time-to-cure was consistently <1 year for thyroid and testicular cancer patients and <10 years for patients with colorectal and cervical cancers, melanoma, and Hodgkin lymphoma. The working group agrees that the evidence allows risk stratification of cancer patients and implementation of personalized care models for timely diagnosis, as well as treatment of possible cancer relapses or related long-term complications, and preventive measures aimed at maintaining health status of cured patients. These aspects should be integrated to produce an appropriate follow-up program and survivorship care plan(s), avoiding stigma and supporting return to work, to a reproductive life, and full rehabilitation. The "right to be forgotten" law, adopted to date only in a few European countries, may contribute to these efforts for cured patients.

Management of Patients with Pancreatic Ductal Adenocarcinoma in the Real-Life Setting: Lessons from the French National Hospital Database

Pancreatic ductal adenocarcinoma (PDAC) remains a major public health challenge, and faces disparities and delays in the diagnosis and access to care. Our purposes were to describe the medical path of PDAC patients in the real-life setting and evaluate the overall survival at 1 year. We used the national hospital discharge summaries database system to analyze the management of patients with newly diagnosed PDAC over the year 2016 in Auvergne-Rhône-Alpes region (AuRA) (France). A total of 1872 patients met inclusion criteria corresponding to an incidence of 22.6 per 100,000 person-year. Within the follow-up period, 353 (18.9%) were operated with a curative intent, 743 (39.7%) underwent chemo- and/or radiotherapy, and 776 (41.4%) did not receive any of these treatments. Less than half of patients were operated in a high-volume center, defined by more than 20 PDAC resections performed annually, mainly university hospitals. The 1-year survival rate was 47% in the overall population. This study highlights that a significant number of patients with PDAC are still operated in low-volume centers or do not receive any specific oncological treatment. A detailed analysis of the medical pathways is necessary in order to identify the medical and territorial determinants and their impact on the patient's outcome.

Cancer cure for 32 cancer types: results from the EUROCARE-5 study

BACKGROUND

Few studies have estimated the probability of being cured for cancer patients. This study aims to estimate population-based indicators of cancer cure in Europe by type, sex, age and period.

METHODS

7.2 million cancer patients (42 population-based cancer registries in 17 European countries) diagnosed at ages 15-74 years in 1990-2007 with follow-up to 2008 were selected from the EUROCARE-5 dataset. Mixture-cure models were used to estimate: (i) life expectancy of fatal cases (LEF); (ii) cure fraction (CF) as proportion of patients with same death rates as the general population; (iii) time to cure (TTC) as time to reach 5-year conditional relative survival (CRS) >95%.

RESULTS

LEF ranged from 10 years for chronic lymphocytic leukaemia patients to <6 months for those with liver, pancreas, brain, gallbladder and lung cancers. It was 7.7 years for patients with prostate cancer at age 65-74 years and >5 years for women with breast cancer. The CF was 94% for testis, 87% for thyroid cancer in women and 70% in men, 86% for skin melanoma in women and 76% in men, 66% for breast, 63% for prostate and <10% for liver, lung and pancreatic cancers. TTC was <5 years for testis and thyroid cancer patients diagnosed below age 55 years, and <10 years for stomach, colorectal, corpus uteri and melanoma patients of all ages. For breast and prostate cancers, a small excess (CRS < 95%) remained for at least 15 years.

CONCLUSIONS

Estimates from this analysis should help to reduce unneeded medicalization and costs. They represent an opportunity to improve patients' quality of life.

On estimating the time to statistical cure

BACKGROUND

The mortality risk among cancer patients measured from the time of diagnosis is often elevated in comparison to the general population. However, for some cancer types, the patient mortality risk will over time reach the same level as the general population mortality risk. The time point at which the mortality risk reaches the same level as the general population is called the cure point and is of great interest to patients, clinicians, and health care planners. In previous studies, estimation of the cure point has been handled in an ad hoc fashion, often without considerations about margins of clinical relevance.

METHODS

We review existing methods for estimating the cure point and discuss new clinically relevant measures for quantifying the mortality difference between cancer patients and the general population, which can be used for cure point estimation. The performance of the methods is assessed in a simulation study and the methods are illustrated on survival data from Danish colon cancer patients.

RESULTS

The simulations revealed that the bias of the estimated cure point depends on the measure chosen for quantifying the excess mortality, the chosen margin of clinical relevance, and the applied estimation procedure. These choices are interdependent as the choice of mortality measure depends both on the ability to define a margin of clinical relevance and the ability to accurately compute the mortality measure. The analysis of cancer survival data demonstrates the importance of considering the confidence interval of the estimated cure point, as these may be wide in some scenarios limiting the applicability of the estimated cure point.

CONCLUSIONS

Although cure points are appealing in a clinical context and has widespread applicability, estimation remains a difficult task. The estimation relies on a number of choices, each associated with pitfalls that the practitioner should be aware of.

The relative survival and cure fraction of gastric cancer estimated through flexible parametric models using data from population-based cancer registration during 2003-2012 in Linzhou, China

PURPOSE

The proportion of cured gastric cancer patients has drawn the attention of patients, physicians, and healthcare providers after comprehensive prevention and control measures were carried out for several years. Therefore, the relative survival and cure fraction were estimated in our study.

METHODS

Population-based cancer registration data were used to estimate survival and cure fraction. A total of 7585 gastric cancer cases (ICD10:C16.0 ~ C16.9) were extracted and included in the final analysis. Cases were diagnosed in 2003-2012 and followed until the end of 2017. Relative survival was calculated as the ratio between the observed survival through the life-table method. The expected survival was estimated by the Ederer II method. The cure fraction was estimated using flexible parametric cure models stratified by age and calendar period when the cases were diagnosed.

RESULTS

The 5-year relative survival of cardia gastric cancer increased with the calendar period of 2003-2004, 2005-2006, 2007-2008, 2009-2010, and 2011-2012 (27.5%, 28.3%, 33.5%, 38.2%, and 46.8%, respectively). The increasing trend along with the calendar periods was also observed in cure proportion of cardia gastric cancer (24.8%, 25.2%, 31.7%, 36.0%, and 43.1%, respectively). Notable improvement of cure proportion was observed in the period of 2011-2012, compared with the initial period of 2003-2004. There was an improvement of 79.8% among all gastric cancer subjects, and it was 74.1% and 55.7% in cardia gastric and noncardia gastric cancer subjects, respectively. The median survival of "uncured" patients showed no significant improvement along with the calendar periods in all age groups.

CONCLUSIONS

Notable improvement of gastric cancer relative survival and cure proportion was observed in Linzhou during 2003-2012.