Claudia Vener1,2*
Silvia Rossi3
Pamela Minicozzi1,4Rafael Marcos-Gragera5,6,7
Hélène A. Poirel8
Marc Maynadié9
Xavier Troussard10
Gabriella Pravettoni2
Roberta De Angelis3†Milena Sant1† the EUROCARE-6 Working Group- 1Analytical Epidemiology and Health Impact Unit, Department of Research, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
- 2Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
- 3Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
- 4Cancer Survival Group, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- 5Epidemiology Unit and Girona Cancer Registry, Oncology Coordination Plan, Department of Health, Autonomous Government of Catalonia, Catalan Institute of Oncology, Girona Biomedical Research Institute (IdiBGi), Universitat de Girona, Girona, Spain
- 6Biomedical Network Research Centers of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- 7Group of Descriptive and Analytical Epidemiology of Cancer, Josep Carreras Leukemia Research Institute, Girona, Spain
- 8Belgian Cancer Registry, Brussels, Belgium
- 9Côte d'Or Hematological Malignancies Registry, Dijon, France
- 10Basse Normandie Cancer Registry, Centre Hospitalier Universitaire (CHU) de Caen, Normandie, Caen, France
Tyrosine kinase inhibitors (TKIs) have been improving the prognosis of patients with chronic myeloid leukemia (CML), but there are still large differences in survival among European countries. This raises questions on the added value of results from population-based studies, which use real-world data, compared to results of randomized controlled trials (RCTs) involving patients with CML. There are also questions about the extent of the findings on RCTs effectiveness for patients in the general population. We compare survival data extracted from our previous systematic review and meta-analysis of CML RCTs with the latest updated population-based survival data of EUROCARE-6, the widest collaborative study on cancer survival in Europe. The EUROCARE-6 CML survival estimated in patients (15–64 years) diagnosed in 2000–2006 vs. 2007–2013 revealed that the prognostic improvement highlighted by RCTs was confirmed in real-world settings, too. The study shows, evaluating for the first time all European regions, that the optimal outcome figures obtained in controlled settings for CML are also achievable (and indeed achieved) in real-world settings with prompt introduction of TKIs in daily clinical practice. However, some differences still persist, particularly in Eastern European countries, where overall survival values are lower than elsewhere, probably due to a delayed introduction of TKIs. Our results suggest an insufficient adoption of adequate protocols in daily clinical practice in those countries where CML survival values remain lower in real life than the values obtained in RCTs. New high-resolution population-based studies may help to identify failures in the clinical pathways followed there.
Highlights
1. The EUROCARE-6 CML survival estimates revealed that the prognostic improvement highlighted by RCTs was confirmed in the European real-world setting.
2. There are still large differences in CML survival throughout Europe: the prompt introduction of TKIs in daily clinical practice is undelayable.
1 Introduction
The European incidence of chronic myeloid leukemia (CML) was about 1.1/100,000 inhabitants (1), increasing to about 4.0/100,000 in patients aged 75–99 at the time of diagnosis. The disease is characterized by the presence of the BCR-ABL1 fusion gene located in the Philadelphia (Ph) chromosome and is classified as being in a chronic (CP), accelerated (AP), or blastic phase (BP), with the last two phases accounting for about 4% and 3% of cases, respectively (2, 3) and being associated with a worse prognosis (4).
For many years, CML was associated with a poor life expectancy (5), but the 2001 introduction of imatinib mesylate, the first tyrosine kinase inhibitor (TKI) and, more recently, of second- and third-generation TKIs (dasatinib, nilotinib, bosutinib, and ponatinib) has profoundly changed the CML curative-intent treatment, previously based on hematopoietic stem cell transplantation. TKIs have greatly improved CML survival rates and now make it possible to consider CML a chronic disease (6–11). Imatinib was approved as first-line treatment for all CML phases and is now available as a generic drug, as its patent has expired. Dasatinib and nilotinib were approved in 2006–2007 as second-line treatments for patients resistant to, or intolerant of, previous treatments (including imatinib): dasatinib in all CML phases and nilotinib only in the CP or AP. Since 2010–2011, both have been authorized for the first-line treatment of newly diagnosed Ph-positive adult cases of CP CML. Bosutinib was licensed in the United States in 2012 (and in Europe in 2013) for the treatment of adults with CP, AP, or BP CML who are resistant to, or intolerant of, previous treatments with one or more TKIs. In December 2017, the recommendation was extended in the United States to include newly diagnosed adult patients with CP CML. Ponatinib was approved in the United States in 2012 (and in Europe in 2013) for the treatment of adults with CP, AP, or BP CML who are resistant to, or intolerant to, other TKIs and also for the treatment of those with CP, AP, or BP CML who have the T315I mutation, which is known to be involved in resistance to all previous TKIs.
The 5-year survival estimates for patients with CML increased from 1997 to 2008 throughout Europe (particularly after 2000), although with large differences among European countries (10, 12): they increased slightly in Southern Europe, more in the United Kingdom, and considerably more in Northern, Central, and Eastern Europe, although in the latter region, survival remained lower than elsewhere (10). These improvements were plausibly linked to the widespread introduction of targeted and other new treatments (10). There was only a small increase in survival estimates among the elderly, possibly because of the under-use of imatinib (90% of patients aged 20–59 received imatinib, 75% of those aged 60–79, and 46% of those aged ≥80) and the newer TKIs (13). Furthermore, the cancer registry (CR) of Girona showed that the 5-year survival rate in patients with CML treated with TKIs in 1994–2008 was about 80%, compared with 44% among those who were not (14).
Population-based studies including all cases occurring in the region covered by a CR reflect the effectiveness of healthcare services in controlling the disease and are more likely to highlight socioeconomic disparities potentially associated with cancer survival. People who live in more affluent areas have better access to optimal care than those living in deprived areas, and this leads to discrepancies in overall survival (OS) figures (15). Moreover, access to optimal treatment is related to per capita income and healthcare investments (16).
Clinical practice, particularly in oncological settings, often relies on randomized controlled trials (RCTs) because they provide more detailed information than population-based studies. However, the amount of data may be overwhelming (17), and it can be difficult to determine the health systems’ sustainability, in terms of finance and uptake of new practices. As a consequence, oncological organizations have developed frameworks to help clinicians and policymakers quantify the real value of new therapies (17–21). Generalizing trial results to everyday clinical practice is not straightforward because of low overall trial accrual (<5% of all newly diagnosed patients with cancer) and under-representation by age, gender, disease stage, co-morbidities, and socioeconomic status. However, despite these limitations, approved treatments are frequently offered to patients who would have been ineligible for the related trials, but they rarely show the benefits detected in RCTs; furthermore, a survival advantage detected by RCTs is not always subsequently confirmed in real-life setting.
This raises questions as to how the results of population-based studies using real-world data can add to the results of RCTs involving patients with CML and to the findings on the extent of RCTs’ effectiveness for the patient population as a whole. In an attempt to answer these questions, we compared the survival of patients with CP CML participating in RCTs with the data from EUROCARE, the widest collaborative population-based study on cancer survival in Europe (22).
2 Materials and Methods
2.1 Study Design
We extracted the survival data from the RCTs included in our previous systematic review and meta-analysis comparing first-line imatinib and second- and third-generation TKIs in adults with newly diagnosed CP CML [International Prospective Register of Systematic Review (PROSPERO) Registration No. CRD42016032903] (Table 1) (58, 59).
Table 1 Summary of the findings of the RCTs included in the meta-analysis.
Population-based survival data were extracted from the EUROCARE-6 dataset (22). ICD-O-3 (International Classification of Disease for Oncology, 3rd edition) (60) morphology codes 9863 (CML with no cytogenetic information or CML not otherwise specified, NOS) and 9875 (CML, BCR-ABL1-positive; Ph+ CML) according to HAEMACARE (61) groupings were selected. Code 9876 (Atypical CML, BCR-ABL1-negative; Ph− aCML) was not included.
Quality and completeness of CRs data were evaluated by applying standardized check procedures in conjunction with the ENCR-JRC technical report, to ensure data comparability (62). At the end of the quality checks of the 101 population-based CRs in the EUROCARE-6 database (that provided continuous incidence data for hematological malignancies from January 1, 2000, to December 31, 2013, with follow-up data up until December 31, 2014), only 84 with adequate information for the purposes of the study (sufficient time coverage, follow-up completeness, and morphology accuracy) were selected (Supplementary Table 1).
The survival analyses were therefore based on 18,083 eligible CML cases, aged between 15 and 64 (the age selection corresponding to the age of patients with CML usually enrolled in RCTs), provided by 84 regional or national CRs in 28 European countries (Table 2). In particular, 8,793 CML cases were diagnosed in 2000–2006 and 9,290 CML cases in 2007–2013. We have defined the threshold of 2006–2007 because it corresponds to the introduction of second-generation TKIs (dasatinib and nilotinib) in clinical practice (first approval in 2006–2007).
Table 2 Myeloid malignancies diagnosed in European patients (15–64 years) in 2000–2013 and quality indicators by Cancer Registry (CR). EUROCARE-6 study dataset.
The EUROCARE-6 patient complete selection is reported in the Supplementary Material.
2.2 Statistical Methods
2.2.1 RCT Meta-Analysis Data
OS data by follow-up time, number of deaths and hazard ratios (HRs), and cancer-specific mortality were collected through the RCTs included in the published meta-analysis (58, 59).
The OS data were pooled using the inverse variance method. Study heterogeneity was evaluated by calculating the I-squared statistic (I2) with little, moderate, and substantial heterogeneity being indicated by I2 values of <50%, 50%–75%, and >75%, respectively. Ninety-five percent confidence intervals (CIs) and two-sided p-values were calculated for each result.
2.2.2 Population-Based Data
Five-year crude OS of CML cases (9863, 9875 ICD-O-3 codes), aged between 15 and 64, diagnosed in 2000–2006 and 2007–2013, by European region and country, was estimated from the EUROCARE-6 study dataset. The 64-year threshold was determined, considering CML RCTs inclusion criteria and to make the age of patients more comparable between RCTs (median age: 50 years; range: 18–91) (Table 1) (58, 59) and population-based EUROCARE-6 results (median age: 50 years) (Table 3). The period of diagnosis threshold (pre- and post-2006) was established considering the timing of second-generation TKIs introduction (dasatinib and nilotinib) in clinical practice.
Table 3 Five-year crude overall survival of CML cases (15–64 years) (9863, 9875 ICD-O-3 codes)1 diagnosed in 2000–2006 and 2007–2013 by European region and country. EUROCARE-6 study dataset.
As most CRs do not collect data concerning disease phase, we used conditional survival (63) to select patients who are potentially in the CP, thus excluding the short-term mortality associated with BP or AP CML. Therefore, conditional crude OS (i.e., the probability of being alive after 5 years, conditional on surviving 3 years after diagnosis, in brief 5-/3-year OS ratio) was computed on the assumption that patients with CML surviving more than 3 years are not likely to include patients in AP and BP.
Relative survival (RS) (64), defined as OS divided by the expected survival of a comparable group (i.e., of the same age, sex and area) from the general population not affected by CML, was estimated using the complete approach (65). Expected survival was estimated using the Ederer II method (66). Conditional crude RS was computed in terms of 5-/3-year RS ratio.
Standard errors (SEs) of OS and RS were derived by applying Greenwood’s formula (67). SE for conditional survival were calculated with the delta method (63). To obtain two-sided 95% CIs, the data were logarithmically transformed. The statistical significance of survival differences between patients diagnosed before and after 2006 (2000–2006 vs. 2007–2013) was tested with the Z-test (68).
2.2.3 Comparison Between RCTs and Population-Based Survival
We compared both OS, including all causes of death for patients with CML, and RS, a proxy of cause-specific survival, i.e., discarding competitive causes of mortality other than CML. Because, for RCTs, RS is not available (as they record the specific cause of death), we estimated the 5-year cause-specific survival (i.e., “freedom from death due to advanced CML”) using data extracted from the corresponding RCTs included in the meta-analysis (58, 59).
The analyses were made using Review Manager v. 5.3 and SEER*Stat software 8.3.9.
3 Results
3.1 RCTs Results
Many of the RCTs did not report OS at each and every one of the time points, but the patients were closely followed-up (Table 1). Only two RCTs reported OS up to 60 months (data not pooled), and only one reported OS up to 72 months. Five-year OS in the ENESTnd (38, 45) study was similar in the imatinib and nilotinib groups [92% vs. 94% for nilotinib of 300 mg (HR = 0.80; 95% CI, 0.43–1.50), and 96% for nilotinib of 400 mg (HR = 0.44; 95% CI, 0.21–0.93)]. Similar results were obtained in the DASISION (23, 32) study comparing imatinib with dasatinib: 5-year OS 90% vs. 91% (HR = 1.01; 95% CI, 0.58–1.73). The first follow-up time point at which it was possible to analyse pooled OS was 36 months (data from three RCTs), but, as it was not clinically relevant, we pooled the HRs roughly extracted from the printed OS curves of Radich et al. (33) (36-month of follow-up) and the ENESTnd (38, 45) and DASISION (23, 32) HRs (60-month follow-up) on the basis of the proportional hazards assumption; the result was not statistically significant (OS: HR = 0.78; 95% CI, 0.54–1.11) (58, 69).
The BFORE study update showed that 5-year OS was similar between bosutinib and imatinib (95% vs. 95%; HR = 0.95; 95% CI, 0.45–1.99) (56).
3.2 EUROCARE-6 Results
The numbers of patients with CML eligible for the survival analysis are reported by CR (Table 2). The main characteristics of patients included in survival analysis and the 5-year crude OS values of all CML cases (9863 - CML NOS, 9875 - Ph+ CML ICD-O-3 codes) are shown by European region and country (Table 3). The 9875 - Ph+ CML ICD-O-3 code is scarcely adopted (22%) (Table 2).
Comparing OS results between the two periods of diagnosis (2000–2006 vs. 2007–2013), a clear increase of OS values was observed for all European regions and for most countries (Table 3). A marked statistically significant increase was observed in the pool of all European countries (71.9% for patients diagnosed in 2000–2006 vs. 84.7% diagnosed in 2007–2013; absolute difference: 12.7%) and in all European areas, with higher improvements (>10%) in Eastern Europe (17.6%) and United Kingdom and Ireland (14.7%). Considering each country, the highest significant increases (>20%) were observed for Wales (21.0%), Slovenia (32.4%), Bulgaria (22.3%), Lithuania (29.5%), and Slovakia (22.8%). Notably, in most Western European countries, OS of patients diagnosed in 2007–2013 was similar to CP CML OS reported in RCTs (Table 1).
The study evaluated crude 5-/3-year conditional OS of all CML cases (i.e., the probability of being alive after 5 years, conditional on surviving 3 years after diagnosis), likely representing patients with CML in CP, diagnosed in 2000–2006 and 2007–2013, by European region and country (Table 4). A significant increase was observed in Europe as a whole (92.9% in 2000–2006 vs. 96.1% in 2007–2013; absolute difference: 3.2%) and in all areas except in Northern and Central Europe, showing that the most substantial 5-year OS increase (12.7%, Table 3) was concentrated in the first 3-year prognosis. Notably, countries with more marked delta OS increases (Slovenia, Lithuania, Bulgaria, and Slovakia; Table 3) showed the highest growth even in the CP (Table 4). Time trends of crude 5-/3-year conditional RS of all CML cases are presented in Supplementary Table 4. Conditional RS values are slightly higher than conditional OS values (by 1.1% on average), reflecting the limited impact of excluding causes of death other than CML in patients aged under 65 at diagnosis. Time trends of conditional RS are quite similar to those estimated for conditional OS. Small significant overall increases were estimated in the European pool (94.0% in 2000–2006 vs. 97.2% in 2007–2013; absolute difference: 3.2%) and in all areas but Northern and Central Europe.
Table 4 Conditional crude 5-/3-year overall survival1 of CML cases (15–64 years) (9863, 9875 ICD-O-3 codes)2 diagnosed in 2000–2006 and 2007–2013 by European region and country. EUROCARE-6 study dataset.
In Supplementary Tables 2, 3 were reported 5-year crude OS and 5-year crude RS, respectively, of CML cases diagnosed in 2000–2006 and 2007–2013 by European region, country, and morphology code. The differences between OS and RS were small, probably due to the patients’ age selection (15–64 years, with negligible competitive mortality). In particular, in Supplementary Table 2, were compared OS values between 9863 CML NOS and 9875 Ph+ CML codes in 2000–2006 and 2007–2013, by areas: in all areas, CML NOS cases showed a lower OS values in comparison with Ph+ CML, even if differences reduced over time (except for Eastern Europe).
3.3 Comparisons Between RCTs and EUROCARE-6 Results
The estimated values of 5-year cause-specific survival in the ENESTnd study were 97.7% (96.0–99.5%) for nilotinib of 300 mg, 98.5% (97.1–100.0%) for nilotinib 400 mg, 93.8% (90.8–96.7%) for imatinib of 400 mg (38, 45). The DASISION study (23, 32) only reported the number of patients who had died of CML-related causes after 5 years of follow-up: 17/260 in the imatinib arm and 9/259 in the dasatinib arm. The estimated values of 5-year cause-specific survival in CP CML RCTs (58, 59) were quite similar to 5-/3-year conditional crude RS of all CML cases estimated in the best ranking countries of the EUROCARE-6 dataset. They are also close to the 5-/3-year conditional crude RS estimates for the European pool (97.2% in 2007–2013) (Supplementary Table 4).
4 Discussion
The comparison of EUROCARE-6 CML survival estimated in patients diagnosed in 2000–2006 vs. 2007–2013 confirmed that the prognostic improvement highlighted by RCTs was verifiable in real-world settings. In particular, the EUROCARE-6 OS values in many countries (Table 3) were very similar to CP CML OS reported in RCTs (Table 1) (58, 59). Moreover, the same brilliant achievement was observed comparing the estimated values of 5-year cause-specific survival in CP CML RCTs (58, 59) with 5-/3-year conditional crude RS estimated in almost all European countries in 2007–2013 (Supplementary Table 4). This means that the optimal outcome figures obtained in controlled settings are achievable (and, indeed, are achieved) in real-world settings, too. The high concordance between CRs and RCTs survival results could be explained by the fact that TKIs are responsible of the quite complete disappearance of AP and BP worse prognosis CML phases. Almost all patients are diagnosed in CP (or have been quickly brought back to CP), so survival results reported in the whole population are close to those of RCTs. Moreover, the high concordance between CRs and RCTs survival results could be related to the fact that we compared quite homogeneous groups of patients with CML aged lower than 65 years with probably few comorbidities.
Previous population studies reported similar or inferior survival results but estimated only on national or small pooled samples.
Swedish CML Registry (779 CMLs, from 2002 to 2010; median age, follow-up: 60 years, 61 months) showed 5-year RS close to 1.0 for those younger than 60 years, 0.9 for those aged 60 to 80 years, and 0.6 for those older than 80 years (70). Swedish Cancer Registry (2,662 CMLs, from 1973 to 2013; median age: 69 years) reported clear improvements in life expectancy over the study period (71). Swedish Cancer Registry and Swedish Cause of Death Registry (CMLs, from 1970 to 2012) showed 5-year OS increasing from 0.18 to 0.82, during the study period; between 2006 and 2012, 5-year RS was close to normal for 40-year-old but considerably lower for 80-year-old patients (72). UK’s Haematological Malignancy Research Network (242 CMLs, from 2004 to 2011; median age: 59 years) showed 5-year OS of 78.9% (72.3% to 84.0%) and 5-year RS of 88.6% (81.0% to 93.3%) (73). Other national studies are aligned with our survival results (74–80).
European Treatment and Outcome Study (EUTOS) (2,904 CMLs, from 2008 to 2013; median age, follow-up: 55 years, 29 months) showed a 30 months OS of 92% (81). US Surveillance, Epidemiology, and End Results (SEER) (13,869 CMLs, from 1975 to 2009) reported lower survival values: 5-year RS ratios increased from 0.26 in 1975–1989 to 0.36 in 1990–2000 and 0.56 in 2001–2009 (82). Moreover, SEER (5,138 CMLs, from 2000 to 2005) showed 5-year OS improvement for all patients during the study period (83, 84). Compared with patients diagnosed in 2000, 5-year OS improved among 15–44 years (from 71.6% to 86.4%), 45–64 years (from 67.5% to 76.3%), 65–74 years (from 38.1% to 51.2%), and 75–84 years patients (from 19.2% to 36.4%) (83).
Population-based studies using real-world survival data reveal differences from the values observed in RCTs that are often related to treatment disparities and largely due to different socioeconomic conditions. They also provide information concerning treatment effectiveness in everyday clinical practice without any patient or outcome selection: they are therefore more representative of what happens in real-life, despite lacking in clinical details offered by RCTs, particularly in relation to disease stage at the time of diagnosis and first-line treatments. The findings of RCTs are often used to guide clinical practice (particularly in oncology), but patient selection can reduce their applicability to the general population (17, 18, 20, 21). Conversely, results of population-based CR studies that fully cover the target population are less affected by patient selection biases, and they provide useful data complementing RCTs outcomes.
However, these two information sources need to be integrated and require the use of new study designs and methods of analysis. High-resolution population-based studies, which include representative patients, present more detailed clinical information than that which is routinely collected by population-based CRs: this approach may help to reduce the gap between RCTs and real-world studies (hrstudies.it; https://www.ipaac.eu/en/work-packages/wp7/).
In an attempt to quantify the difference between RCTs and population-based studies using tangible data, we compared OS and cause-specific survival observed in the RCTs included in our previous systematic review (58), and OS and RS values estimated using EUROCARE-6 (22) cases diagnosed up to age 64 over a comparable period of time. It was the first time that this was done for CML, considering all European regions and pooling survival results. Our study shows that CML survival values tend to become very similar between RCTs and population-based settings, regardless of the survival analysis methods used. However, some differences still persist, in particular in Eastern European countries, where OS values were lower than elsewhere, especially in the first period of time being considered: this is probably due to a delayed introduction of TKIs in daily clinical practice. To underline that the date of the introduction of TKIs reimbursement varied greatly between Europe: this could be useful to interpret the different survival outcomes observed by countries (Supplementary Table 5). Also to notice that the allogeneic bone marrow transplantations medium rate was 0.62 per million for Eastern European countries in comparison with 0.81 per million for other European countries [Supplementary Table 6, by calendar year from 2000 to 2022 and by country; data provided by the European Society for Blood and Marrow Transplantation (EBMT), Chronic Malignancies Working Party (CMWP)].
Residual discrepancies can be attributed to different case selection criteria: RCTs select patients on the basis of well-defined inclusion and exclusion criteria, and the results cannot be readily extended to the general population, whereas population-based studies involve unselected patients but often lack detail and, in the case of CML, the morphology code might be not very precise. Moreover, RCTs almost always record cancer-specific mortality, with off-study survival being reported by the investigator after study discontinuation, whereas population studies systematically update life status of all registered patients and use RS to make adjustments for general mortality by age, gender, and geographical area.
RCTs also generally include patients without comorbidities who are younger than those encountered in real-life populations: for example, it has been found that the elderly, women, and members of racial and ethnic minorities are less likely to be enrolled in American cooperative group cancer trials than patients who are younger, male, and Caucasian (85, 86).
Our previous meta-analysis did not reveal any difference in the OS of patients treated with the first- or the new-generation TKIs (58, 59). In the only two RCTs for which 5-year OS data are available [DASISION (23, 32) and ENESTnd (38, 45)], the 60-month OS value was similar in the patients treated with imatinib and those treated with dasatinib or nilotinib, and similar to EUROCARE-6 OS data for patients diagnosed in 2007–2013. To underline that second-generation TKIs introduction time in clinical practice (2006–2007) limits a strict comparison with survival data of previous years, but imatinib can be considered an historical arm because it has been introduced in 2001. Moreover, CML survival values under imatinib or second-generation TKIs are fairly superimposable (60 months RCTs OS ≥ 90%, Table 1).
We compared the first-line treatment of RCT patients with newly diagnosed CP CML with all treatment lines administered to patients with CML from the general population (including a small percentage of patients with AP and BP CML who have a different prognosis). Unfortunately, CRs do not routinely collect information on CML phase and treatment line; thus, it was not possible to select CP CML cases receiving first-line treatment. To overcome this drawback, we analyzed 5-/3-year conditional OS and RS to remove the contribution of BP and AP CML and improve estimates comparability. Considering conditional OS and RS for patients diagnosed in 2007–2013, population-based CRs survival values were very similar to those observed in the RCTs.
Code 9876 (Ph− atypical CML or aCML) was not included but, as most CRs do not distinguish Ph+ CML and Ph− aCML, and as 78.0% of cases are classified as CML NOS (Table 2), some aCML cases were inevitably included. This has little impact on our analysis as 90%–95% of CML diagnoses have the characteristic t(9;22)(q34;q11.2) reciprocal translocation, leading to the Ph chromosome and to the BCR-ABL1 fusion gene that is the target for specific TKIs (4). However, this partly explains why OS values for ICD-O-3 code 9863, including CML NOS and (probably) patients with poorer prognosis (such as aCML cases not targeted by TKIs), were, at all evaluable times and in all evaluable regions, lower compared to the values for Ph+ CML for which TKIs are indicated.
Code 9875 (Ph+ CML) was hardly used in Northern Europe or the United Kingdom and Ireland, and the implausibly small number of cases in the other regions/countries considered is attributable to differences in registration criteria or inaccurate pathological description. It is also likely that the underuse of code 9875 for Ph+ CML is due to a bad translation of the ICD-O-3 classification: code 9863 refers to “chronic myeloid leukemia, NOS” and code 9875 refers to “chronic myelogenous leukemia, BCR/ABL positive” (Ph+ CML) and, although hematologists normally correctly diagnose cases of code 9875 as Ph+ CML, the use of the word “myelogenous” is ambiguous for non-hematologists. This may also explain the considerable difference in the use of code 9875 between specialized hematological registries and general CRs. CRs should correctly code CML morphology by specifying ICD-O-3 9875 (Ph+ CML) or 9876 (Ph− aCML), the phase of the disease at the time of diagnosis, first-line therapy, and the occurrence of transformation into AP or BP to make a more precise analysis possible: one that is potentially comparable with other types of studies. Some strategies should be adopted to avoid CML code misuse and to reduce the number of CML NOS cases, such as to plan specific training courses to increase the precision of coding or to link CML population-based data with other available data sources, for example, national health insurance databases, to discover patients really treated with TKIs (87). Unfortunately, 9875 (Ph+ CML) code is so underused in CRs in the studied period 2000–2013 not to permit to design a population-based study excluding 9863 code (CML NOS).
A clear improvement in real-world CML survival was observed in European regions and countries comparing EUROCARE-6 with RCTs OS data. However, some discrepancies with RCTs still remain. Our results suggest an insufficient adoption of adequate protocols in daily clinical practice in countries where CML survival values still remain lower in real-life than those obtained in RCTs. In future works, it will be of interest to focus on populations usually excluded from RCTs, such as older patients, or with comorbidities and other cancers.
EUROCARE-6 Working Group
Austria: M. Hackl (National CR); Belgium: E. Van Eycken (National CR); Bulgaria: Z. Valerianova (National CR); Croatia: M. Sekerija (National CR); Cyprus: P. Pavlou (National CR); Czech Republic: L. Dušek (National CR); Denmark: H. Storm (National CR); Estonia: M. Mägi; K. Innos* (National CR); Finland: N. Malila; J. Pitkäniemi (National CR); France: M. Velten (Bas Rhin CR); X. Troussard (Basse Normandie, Haematological Malignancies CR); A.M. Bouvier; V. Jooste* (Burgundy, Digestive CR); A.V. Guizard (Calvados, General CR); G. Launoy (Calvados, Digestive CR); S. Dabakuyo Yonli (Cote dOr, Gynaecologic (Breast) CR); M. Maynadié (Cote dOr, Haematological Malignancies CR); A.S. Woronoff (Doubs CR); J.B. Nousbaum (Finistere, Digestive CR); G. Coureau (Gironde, General CR); A. Monnereau* (Gironde, Haematological Malignancies CR); I. Baldi (Gironde, Central Nervous System CR); K. Hammas (Haut-Rhin CR); B. Tretarre (Herault CR); M. Colonna (Isere CR); S. Plouvier (Lille Area CR); T. D’Almeida (Limousin CR); F. Molinié; A. Cowppli-Bony (Loire-Atlantique/Vendée CR); S. Bara (Manche CR); C. Schvartz (Marne-Ardennes, Thyroid CR); G. Defossez (Poitou-Charentes CR); B. Lapôtre-Ledoux (Somme CR); P. Grosclaude (Tarn CR); Germany: S. Luttmann (Bremen CR); R. Stabenow [Common CR of 4 Federal States (Brandenburg, Mecklenburg-West Pomerania, Saxony-Anhalt, Thüringen)]; A. Nennecke (Hamburg CR); J. Kieschke (Lower Saxony CR); S. Zeissig (Rhineland-Palatinate CR); B. Holleczek (Saarland CR); A. Katalinic* (Schleswig-Holstein CR); Iceland: H. Birgisson (National CR); Ireland: D. Murray; P.M. Walsh (National CR); Italy: G. Mazzoleni; F. Vittadello (Alto Adige CR); F. Cuccaro (Barletta-Andria-Trani CR); R. Galasso (Basilicata CR); G. Sampietro (Bergamo CR); S. Rosso (Biella CR); M. Magoni (Brescia CR); M. Ferrante (Catania-Messina-Enna CR); A. Sutera Sardo (Catanzaro CR); M.L. Gambino (Como CR); P. Ballotari; E. Giacomazzi (Cremona and Mantova CR); S. Ferretti (Ferrara CR); A. Caldarella; G. Manneschi (Firenze-Prato CR); G. Gatta*; M. Sant*; P. Baili*; F. Berrino*; L. Botta; A. Trama; R. Lillini; A. Bernasconi; S. Bonfarnuzzo; C. Vener; F. Didonè; P. Lasalvia; G. Del Monego; M.C. Magri; L. Buratti (Fondazione IRCCS Istituto Nazionale dei Tumori, Milan); D. Serraino; L. Dal Maso (Friuli Venezia Giulia CR); R. Capocaccia* (Epidemiologia e Prevenzione Board); R. De Angelis*; E. Demuru; C. Di Benedetto; S. Rossi*; M. Santaquilani; S. Venanzi (Istituto Superiore di Sanità, Rome); R.A. Filiberti (Genova CR); S. Iacovacci (Latina CR); V. Gennaro (Liguria, mesotheliomas CR); A.G. Russo (Lodi CR); G. Spagnoli (Modena CR); L. Cavalieri d’Oro (Monza and Brianza CR); M. Fusco; M.F. Vitale (Napoli CR); M. Usala (Nuoro CR); F. Vitale (Palermo CR); M. Michiara (Parma CR); G. Chiranda (Piacenza CR); G. Cascone; E. Spata (Ragusa CR); L. Mangone (Reggio Emilia CR); F. Falcini (Romagna CR); R. Cavallo (Salerno CR); D. Piras (Sassari CR); A. Madeddu; F. Bella (Siracusa CR); A.C. Fanetti (Sondrio CR); S. Minerba (Taranto CR); G. Candela; T. Scuderi (Trapani CR); R.V. Rizzello (Trento CR); F. Stracci (Umbria CR); G. Tagliabue (Varese CR); M. Rugge (Veneto CR); A. Brustolin (Viterbo CR); Latvia: S. Pildava (National CR); Lithuania: G. Smailyte (National CR); Malta: M. Azzopardi (National CR); Norway: T.B. Johannesen* (National CR); Poland: J. Didkowska; U. Wojciechowska (National CR); M. Bielska-Lasota* (National Institute of Public Health-National Institute of Hygiene-National Research Institute, Warsaw); Portugal: A. Pais (Central Portugal CR); J.L. Pontes (Northern Portugal CR); A. Miranda (Southern Portugal CR); Slovakia: C. Safaei Diba (National CR); Slovenia: V. Zadnik; T. Zagar (National CR); Spain: C. Sánchez-Contador Escudero; P. Franch Sureda (Balearic Islands, Mallorca CR); A. Lopez de Munain; M. De-La-Cruz (Basque Country CR); M.D. Rojas, A. Aleman (Canary Islands CR); A. Vizcaino (Castellon CR); R. Marcos-Gragera (Girona CR); M.J. Sanchez (Granada CR); M.D. Chirlaque (Murcia CR); M. Guevara Eslava*; E. Ardanaz (Navarra CR); J. Galceran; M. Carulla (Tarragona CR); Switzerland: Y. Bergeron (Fribourg CR); C. Bouchardy (Geneva CR); S. Mohsen Mousavi (Graubünden and Glarus CR); S. Mohsen Mousavi (Eastern Switzerland CR); A. Bordoni (Ticino CR); The Netherlands: O. Visser* (National CR); UK-England: J. Rashbass (National CR); UK-Northern Ireland: A. Gavin* (National CR); UK-Scotland: D. Morrison (National CR); UK-Wales: D. W. Huws* (National CR).*EUROCARE Steering Committee
Data Availability Statement
The datasets presented in this article are not readily available. See EUROCARE-6 Collaborative Group Rules (http://www.eurocare.it). Requests to access the datasets should be directed to http://www.eurocare.it.
Ethics Statement
Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the participants’ legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.
Author Contributions
CV designed and carried out the study and analyzed the data; SR and PM did quality controls and analyzed the data; RA and MS designed the study and data quality checks; RM-G, HP, MM, XT, and GP provided advice and revised the results. EUROCARE-6 Working Group collected, prepared, and transmitted raw data for the study database; corrected data after quality controls; and checked the results of the analyses. All authors contributed to the article and approved the submitted version.
Funding
This study was funded by the Compagnia di San Paolo, the Cariplo Foundation and the European Commission (grant number 801520 HP-JA-2017, Innovative Partnership for Action Against Cancer, iPAAC Joint Action). The sources of the funding played no role in designing the study, collecting, analyzing, or interpreting the data, writing the report, or deciding whether or not to submit the article for publication. This research was (partially) funded by Italian Ministry of Health “Ricerca Corrente” funds.
Conflict of Interest
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.
Publisher’s Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Acknowledgments
We would like to thank Simone Bonfarnuzzo for his assistance and Christine Gislason for revising the language of the paper.
Supplementary Material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2022.892684/full#supplementary-material
References
1. Sant M, Allemani C, Tereanu C, De Angelis R, Capocaccia R, Visser O, et al. Incidence of Hematologic Malignancies in Europe by Morphologic Subtype: Results of the HAEMACARE Project. Blood (2010) 116:3724–34. doi: 10.1182/blood-2010-05-282632
2. Björkholm M, Ohm L, Eloranta S, Derolf A, Hultcrantz M, Andersson JST, et al. Success Story of Targeted Therapy in Chronic Myeloid Leukemia: A Population-Based Study of Patients Diagnosed in Sweden From 1973 to 2008. JCO (2011) 29:2514–20. doi: 10.1200/JCO.2011.34.7146
3. Hoffmann VS, Baccarani M, Hasford J, Lindoerfer D, Burgstaller S, Sertic D, et al. The EUTOS Population-Based Registry: Incidence and Clinical Characteristics of 2904 CML Patients in 20 European Countries. Leukemia (2015) 29:1336–43. doi: 10.1038/leu.2015.73
4. Swerdlow SH, Campo E, NL H, Jaffe ES, Pileri SA, Stein H, et al. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. Lyon, France: IARC Press (2008).
5. Silver RT, Woolf SH, Hehlmann R, Appelbaum FR, Anderson J, Bennett C, et al. An Evidence-Based Analysis of the Effect of Busulfan, Hydroxyurea, Interferon, and Allogeneic Bone Marrow Transplantation in Treating the Chronic Phase of Chronic Myeloid Leukemia: Developed for the American Society of Hematology. Blood (1999) 94:1517–36.
6. Druker BJ, Talpaz M, Resta DJ, Peng B, Buchdunger E, Ford JM, et al. Efficacy and Safety of a Specific Inhibitor of the BCR-ABL Tyrosine Kinase in Chronic Myeloid Leukemia. N Engl J Med (2001) 344:1031–7. doi: 10.1056/NEJM200104053441401
7. Druker BJ, Tamura S, Buchdunger E, Ohno S, Segal GM, Fanning S, et al. Effects of a Selective Inhibitor of the Abl Tyrosine Kinase on the Growth of Bcr-Abl Positive Cells. Nat Med (1996) 2:561–6. doi: 10.1038/nm0596-561
8. Buchdunger E, Zimmermann J, Mett H, Meyer T, Müller M, Druker BJ, et al. Inhibition of the Abl Protein-Tyrosine Kinase In Vitro and In Vivo by a 2-Phenylaminopyrimidine Derivative. Cancer Res (1996) 56:100–4.
9. Druker BJ. Perspectives on the Development of a Molecularly Targeted Agent. Cancer Cell (2002) 1:31–6. doi: 10.1016/S1535-6108(02)00025-9
10. Sant M, Minicozzi P, Mounier M, Anderson LA, Brenner H, Holleczek B, et al. Survival for Haematological Malignancies in Europe Between 1997 and 2008 by Region and Age: Results of EUROCARE-5, a Population-Based Study. Lancet Oncol (2014) 15:931–42. doi: 10.1016/S1470-2045(14)70282-7
11. Francis S, Lucas C, Lane S, Wang L, Watmough S, Knight K, et al. A Population Study Showing That the Advent of Second Generation Tyrosine Kinase Inhibitors has Improved Progression-Free Survival in Chronic Myeloid Leukaemia. Leuk Res (2013) 37:752–8. doi: 10.1016/j.leukres.2013.04.003
12. De Angelis R, Minicozzi P, Sant M, Dal Maso L, Brewster DH, Osca-Gelis G, et al. Survival Variations by Country and Age for Lymphoid and Myeloid Malignancies in Europe 2000-2007: Results of EUROCARE-5 Population-Based Study. EJC (2015) 51:2254–68. doi: 10.1016/j.ejca.2015.08.003
13. Wiggins CL, Harlan LC, Nelson HE, Stevens JL, Willman CL, Libby EN, et al. Age Disparity in the Dissemination of Imatinib for Treating Chronic Myeloid Leukemia. Am J Med (2010) 123:764.e1–9. doi: 10.1016/j.amjmed.2010.03.018
14. Osca-Gelis G, Puig-Vives M, Saez M, Gallardo D, Lloveras N, Guárdia R, et al. Is Survival in Myeloid Malignancies Really Improving? A Retrospective 15 Year Population-Based Study. Leuk Lymphoma (2015) 56:896–902. doi: 10.3109/10428194.2014.947610
15. Marmot M. Fair Society, Healthy Lives. The Marmot Review. Strategic Review of Health Inequalities in England Post-2010. Available at: http://www.instituteofhealthequity.org (Accessed Nov 11, 2021).
16. Baili P, Di Salvo F, Marcos-Gragera R, Siesling S, Mallone S, Santaquilani M, et al. Age and Case Mix-Standardised Survival for All Cancer Patients in Europe 1999-2007: Results of EUROCARE-5, a Population-Based Study. Eur J Cancer (2015) 51:2120–9. doi: 10.1016/j.ejca.2015.07.025
17. Del Paggio JC. Deconstructing Clinical Trials-Help From Oncology Value Frameworks. JAMA Oncol (2017) 3:1306–7. doi: 10.1001/jamaoncol.2017.1312
18. Chandra A, Shafrin J, Dhawan R. Utility of Cancer Value Frameworks for Patients, Payers, and Physicians. JAMA (2016) 315:2069–70. doi: 10.1001/jama.2016.4915
19. Hellmann MD, Kris MG, Rudin CM. Medians and Milestones in Describing the Path to Cancer Cures: Telling “Tails”. JAMA Oncol (2016) 2:167–8. doi: 10.1001/jamaoncol.2015.4345
20. Vera-Badillo FE, Napoleone M, Krzyzanowska MK, Alibhai SMH, Chan AW, Ocana A, et al. Bias in Reporting of Randomised Clinical Trials in Oncology. Eur J Cancer (2016) 61:29–35. doi: 10.1016/j.ejca.2016.03.066
21. Tannock IF, Amir E, Booth CM, Niraula S, Ocana A, Seruga B, et al. Relevance of Randomised Controlled Trials in Oncology. Lancet Oncol (2016) 17:e560–7. doi: 10.1016/S1470-2045(16)30572-1
22. EUROCARE Survival of Cancer Patients in Europe. Available at: http://www.eurocare.it (Accessed Nov 11, 2021).
23. Kantarjian HM, Shah NP, Hochhaus A, Cortes J, Shah S, Ayala M, et al. Dasatinib Versus Imatinib in Newly Diagnosed Chronic-Phase Chronic Myeloid Leukemia. N Engl J Med (2010) 362(24):2260–70. doi: 10.1056/NEJMoa1002315
24. Shah N, Kantarjian HM, Hochhaus A, Cortes JE, Bradley-Garelik MB, Zhu C, et al. Dasatinib Versus Imatinib in Patients With Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-CP) in the DASISION Trial: 18-Month Follow-Up. Blood (ASH Annu Meeting Abstracts) (2010) 116(21):206. doi: 10.1182/blood.V116.21.206.206
25. Kantarjian HM, Shah NP, Cortes JE, Baccarani M, Bradley-Garelik MB, ZhuA C, et al. Dasatinib or Imatinib (IM) in Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-CP): Two-Year Follow-Up From DASISION. J Clin Oncol (ASCO Annu Meeting Abstracts) (2011) 29(15):6510. doi: 10.1200/jco.2011.29.15_suppl.6510
26. Hochhaus A, Saglio G, Chuah C, Pavlovsky C, Bradley Garelick MB, Lambert A, et al. Dasatinib and Imatinib-Induced Reductions in BCR-ABL Transcript Levels Below 10% at 3 Months Are Associated With Improved Responses in Patients With Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-CP): Analysis of Molecular Response Kinetics in the DASISION Trial. [Abstract]. Blood (ASH Annu Meeting Abstracts) (2011) 118(21):2767. doi: 10.1182/blood.V118.21.2767.2767
27. Hochhaus A, Shah N, Cortes JE, Baccarani M, Bradley-Garelik MB, Dejardin D, et al. Dasatinib Versus Imatinib (IM) in Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-CP): DASISION 3-Year Follow-Up. J Clin Oncol (ASCO Annu Meeting Abstracts) (2012) 30(15):6504. doi: 10.1200/jco.2012.30.15_suppl.6504
28. Kantarjian HM, Shah NP, Cortes JE, Baccarani M, Agarwal MB, Undurraga MS, et al. Dasatinib or Imatinib in Newly Diagnosed Chronic-Phase Chronic Myeloid Leukemia: 2-Year Follow-Up From a Randomized Phase 3 Trial (DASISION). Blood (2012) 119(5):1123–9. doi: 10.1182/blood-2011-08-376087
29. Jabbour E, Kantarjian HM, Saglio G, Steegmann JL, Shah NP, Boqué C, et al. Early Response With Dasatinib or Imatinib in Chronic Myeloid Leukemia: 3-Year Follow-Up From a Randomized Phase 3 Trial (DASISION). Blood (2014) 123(4):494–500. doi: 10.1182/blood-2013-06-511592
30. Cortes JE, Hochhaus A, Kim DW, Shah NP, Mayer J, Rowlings P, et al. Four-Year (Yr) Follow-Up of Patients (Pts) With Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-CP) Receiving Dasatinib or Imatinib: Efficacy Based on Early Response. Blood (ASH Annu Meeting Abstracts) (2013) 122(21):653. doi: 10.1182/blood.V122.21.653.653
31. Cortes JE, Saglio G, Baccarani M, Kantarjian HM, Mayer J, Boqué C, et al. Final Study Results of the Phase 3 Dasatinib Versus Imatinib in Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-CP) Trial (DASISION, CA180-056). Blood (ASH Annu Meeting Abstracts) (2014) 124(21):152. doi: 10.1182/blood.V124.21.152.152
32. Cortes JE, Saglio G, Kantarjian HM, Baccarani M, Mayer J, Boqué C, et al. Final 5-Year Study Results of DASISION: The Dasatinib Versus Imatinib Study in Treatment-Naïve Chronic Myeloid Leukemia Patients Trial. J Clin Oncol (2016) 34(20):2333–40. doi: 10.1200/JCO.2015.64.8899
33. Radich JP, Kopecky KJ, Appelbaum FR, Kamel-Reid S, Stock W, Malnassy G, et al. A Randomized Trial of Dasatinib 100 Mg Versus Imatinib 400 Mg in Newly Diagnosed Chronic-Phase Chronic Myeloid Leukemia. Blood (2012) 120(19):3898–905. doi: 10.1182/blood-2012-02-410688
34. Mustjoki S, Richter J, Barbany G, Ehrencrona H, Fioretos T, Gedde-Dahl T, et al. Impact of Malignant Stem Cell Burden on Therapy Outcome in Newly Diagnosed Chronic Myeloid Leukemia Patients. Leukemia (2013) 27(7):1520–6. doi: 10.1038/leu.2013.19
35. Hjorth-Hansen H, Richter J, Stenke L, Ehrencrona H, Gjertsen BT, Gedde-Dahl T, et al. Dasatinib Treatment Induces Fast and Deep Responses in Newly Diagnosed Chronic Myeloid Leukemia (CML) Patients in Chronic Phase: Clinical Results From a Randomised Phase-2 Study (Nordcml006). Blood (ASH Annu Meeting Abstracts) (2013) 122(21):4032. doi: 10.1182/blood.V122.21.4032.4032
36. Hjorth-Hansen H, Stenke L, Söderlund S, Dreimane A, Ehrencrona H, Gedde-Dahl T, et al. Dasatinib Induces Fast and Deep Responses in Newly Diagnosed Chronic Myeloid Leukaemia Patients in Chronic Phase: Clinical Results From a Randomised Phase-2 Study (Nordcml006). Eur J Haematol (2015) 94(3):243–50. doi: 10.1111/ejh.12423
37. Larson RA, Le Coutre PD, Reiffers J, Hughes TP, Saglio G, Edrich P, et al. Comparison of Nilotinib and Imatinib in Patients (Pts) With Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-CP): ENESTnd Beyond One Year. J Clin Oncol (ASCO Annu Meeting Abstracts) (2010) 28(15):6501. doi: 10.1200/jco.2010.28.15_suppl.6501
38. Saglio G, Kim DW, Issaragrisil S, le Coutre P, Etienne G, Lobo C, et al. Nilotinib Versus Imatinib for Newly Diagnosed Chronic Myeloid Leukemia. N Engl J Med (2010) 362(24):2251–9. doi: 10.1056/NEJMoa0912614
39. Hughes T, Hochhaus A, Saglio G, Kim DW, Jootar S, Le Coutre PD, et al. ENESTnd update: Continued Superiority of Nilotinib Versus Imatinib in Patients with Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-CP). Blood (ASH Annual Meeting Abstracts) (2010) 116(21). [Abstract 207].
40. Kantarjian HM, Hochhaus A, Saglio G, De Souza C, Flinn IW, Stenke L, et al. Nilotinib Versus Imatinib for the Treatment of Patients With Newly Diagnosed Chronic Phase, Philadelphia Chromosome-Positive, Chronic Myeloid Leukaemia: 24-Month Minimum Follow-Up of the Phase 3 Randomised ENESTnd Trial. Lancet Oncol (2011) 12(9):841–51. doi: 10.1016/S1470-2045(11)70201-7
41. Kantarjian HM, Kim DW, Issaragrisil S, Clark RE, Reiffers J, Nicolini FE, et al. Enestnd 4-Year (Y) Update: Continued Superiority of Nilotinib vs Imatinib in Patients (Pts) With Newly Diagnosed Philadelphia Chromosome-Positive (Ph+) Chronic Myeloid Leukemia in Chronic Phase (CML-CP). [Abstract]. Blood (ASH Annu Meeting Abstracts) (2012) 120(21):1676. doi: 10.1182/blood.V120.21.1676.1676
42. Larson RA, Hochhaus A, Hughes TP, Clark RE, Etienne G, Kim DW, et al. Nilotinib vs Imatinib in Patients With Newly Diagnosed Philadelphia Chromosome-Positive Chronic Myeloid Leukemia in Chronic Phase: ENESTnd 3-Year Follow-Up. Leukemia (2012) 26(10):2197–203. doi: 10.1038/leu.2012.134
43. Hochhaus A, Saglio G, Larson RA, Kim DW, Etienne G, Rosti G, et al. Nilotinib Is Associated With a Reduced Incidence of BCR-ABL Mutations vs Imatinib in Patients With Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase. Blood (2013) 121(18):3703–8. doi: 10.1182/blood-2012-04-423418
44. Hughes TP, Saglio G, Kantarjian HM, Guilhot F, Niederwieser D, Rosti G, et al. Early Molecular Response Predicts Outcomes in Patients With Chronic Myeloid Leukemia in Chronic Phase Treated With Frontline Nilotinib or Imatinib. Blood (2014) 123(9):1353–60. doi: 10.1182/blood-2013-06-510396
45. Hochhaus A, Saglio G, Hughes TP, Larson RA, Kim DW, Issaragrisil S, et al. Long-Term Benefits and Risks of Frontline Nilotinib vs Imatinib for Chronic Myeloid Leukemia in Chronic Phase: 5-Year Update of the Randomized ENESTnd Trial. Leukemia (2016) 30(5):1044–54. doi: 10.1038/leu.2016.5
46. Hochhaus A, Saglio G, Hughes TP, Larson RA, Taningco L, Deng W, et al. Impact of Treatment With Frontline Nilotinib (NIL) vs Imatinib (IM) on Sustained Deep Molecular Response (MR) in Patients (Pts) With Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase (CML-Cp). Blood (ASH Annu Meeting Abstracts) (2015) 126(23):2781. doi: 10.1182/blood.V126.23.2781.2781
47. Hughes T, Larson RA, Kim DW, Issaragrisil S, Le Coutre PD, Lobo C, et al. Efficacy and Safety of Nilotinib vs Imatinib in Patients With Newly Diagnosed Chronic Myeloid Leukemia in Chronic Phase: 6-Year Follow-Up of ENESTND. Haematologica (EHA-European Hematol Assoc Library) (2015) 100480:P228.
48. Cortes JE, DW K, Kantarjian HM, Brümmendorf TH, Dyagil I, Griskevicius L, et al. Bosutinib Versus Imatinib in Newly Diagnosed Chronic-Phase Chronic Myeloid Leukemia: Results From the BELA Trial. J Clin Oncol (2012) 30(28):3486–92. doi: 10.1200/JCO.2011.38.7522
49. Gambacorti-Passerini C, Cortes JE, Kim DW, Kantarjian H, Khattry N, Lipton JH, et al. Bosutinib (BOS) Versus Imatinib (IM) in Patients (Pts) With Chronic Phase Chronic Myeloid Leukemia (CP CML) in the BELA Trial: 18-Month Follow-Up. J Clin Oncol (ASCO Annu Meeting Abstracts) (2011) 29(15):6509. doi: 10.1200/jco.2011.29.15_suppl.6509
50. Brümmendorf TH, Cortes JE, De Souza CA, Guilhot F, Duvillié L, Pavlov D, et al. Bosutinib Versus Imatinib in Newly Diagnosed Chronic-Phase Chronic Myeloid Leukaemia: Results From the 24-Month Follow-Up of the BELA Trial. Br J Haematol (2015) 168(1):69–81. doi: 10.1111/bjh.13108
51. Brümmendorf TH, Gambacorti-Passerini C, Lipton J, Tee GY, Casado LF, Zaritskey A, et al. Bosutinib Versus Imatinib in Newly Diagnosed Chronic-Phase Chronic Myeloid Leukaemia: 30-Month Update of the BELA Trial. Haematologica (EHA-European Hematol Assoc Meeting Abstracts) (2012) 97(s1):0587.
52. Gambacorti-Passerini C, JE C, JH L, Dmoszynska A, Wong RS, Rossiev V, et al. Safety of Bosutinib Versus Imatinib in the Phase 3 BELA Trial in Newly Diagnosed Chronic Phase Chronic Myeloid Leukemia. Am J Hematol (2014) 89(10):947–53. doi: 10.1002/ajh.23788
53. Cortes JE, Jean Khoury H, Kantarjian H, Brümmendorf TH, Mauro MJ, Matczak E, et al. Long-Term Evaluation of Cardiac and Vascular Toxicity in Patients With Philadelphia Chromosome-Positive Leukemias Treated With Bosutinib. Am J Hematol (2016) 91(6):606–16. doi: 10.1002/ajh.24360
54. Cortes JE, Gambacorti-Passerini C, Deininger MW, Mauro MJ, Chuah C, Kim DW, et al. Bosutinib Versus Imatinib for Newly Diagnosed Chronic Myeloid Leukemia: Results From the Randomized BFORE Trial. J Clin Oncol (2018) 36(3):231–7. doi: 10.1200/JCO.2017.74.7162
55. Gambacorti-Passerini C, Deininger MW, Mauro MJ, Chuah C, Kim DW, Dyagil I, et al. Bosutinib vs Imatinib for Newly Diagnosed Chronic Myeloid Leukaemia (CML) in the BFORE Trial: 18-Month Follow-Up. Blood (ASH Annu Meeting Abstracts) (2017) 130(1):896. doi: 10.1182/blood.V130.Suppl_1.896.896
56. Brümmendorf TH, Cortes JE, Milojkovic D, Gambacorti-Passerini C, Clark RE, le Coutre PD, et al. Bosutinib (BOS) Versus Imatinib for Newly Diagnosed Chronic Phase (CP) Chronic Myeloid Leukemia (CML): Final 5-Year Results From the Bfore Trial. Blood (ASH Annu Meeting Abstracts) (2020) 136(1):41. doi: 10.1182/blood-2020-137393
57. Lipton JH, Chuah C, Guerci-Bresler A, Rosti G, Simpson D, Assouline S, et al. Ponatinib Versus Imatinib for Newly Diagnosed Chronic Myeloid Leukaemia: An International, Randomised, Open-Label, Phase 3 Trial. Lancet Oncol (2016) 17(5):612–21. doi: 10.1016/S1470-2045(16)00080-2
58. Vener C, Banzi R, Ambrogi F, Ferrero A, Saglio G, Pravettoni G, et al. First-Line Imatinib Versus 2nd and 3rd Generation TKIs for Chronic Phase CML: Systematic Review and Meta-Analysis. Blood Adv (2020) 4(12):2723–35. doi: 10.1182/bloodadvances.2019001329
59. Vener C, Ferrero A, Banzi R, Pistotti V, Del Giovane C, Sant M, et al. Available at: http://www.crd.york.ac.uk/PROSPERO/ (Accessed Nov 11, 2021).
60. Fritz A, Percy C, Jack A, Shanmugaratnam K, Sobin L, Parkin DM, et al. International Classification of Disease for Oncology (ICD-O), 3rd Edn. Geneva: World Health Organization (2000).
61. HAEMACARE Working Group. Manual for Coding and Reporting Haematological Malignancies. Tumori (2010) 96(4):i–A32.
62. Martos C, Crocetti E, Visser O, Rous B. Giusti F and the Cancer Data Quality Checks Working Group. A Proposal on Cancer Data Quality Checks. In: One Common Procedure for European Cancer Registries - Version 1.1. Luxembourg: Publications Office of the European Union (2018).
63. Janssen-Heijnen ML, Gondos A, Bray F, Hakulinen T, Brewster DH, Brenner H, et al. Clinical Relevance of Conditional Survival of Cancer Patients in Europe: Age-Specific Analyses of 13 Cancers. J Clin Oncol (2010) 28:2520–8. doi: 10.1200/JCO.2009.25.9697
64. Rossi S, Baili P, Capocaccia R, Caldora M, Carrani E, Minicozzi P, et al. The EUROCARE-5 Study on Cancer Survival in Europe 1999-2007: Database, Quality Checks and Statistical Analysis Methods. Eur J Cancer (2015) 51(15):2104–19. doi: 10.1016/j.ejca.2015.08.001
65. Brenner H, Gefeller O, Hakulinen T. Period Analysis for ‘Up-Todate’ Cancer Survival Data: Theory, Empirical Evaluation, Computational Realisation and Applications. Eur J Cancer (2004) 40:326–35. doi: 10.1016/j.ejca.2003.10.013
66. Ederer F, Axtell LM, Cutler SJ. The Relative Survival: A Statistical Methodology. Natl Cancer Inst Monogr (1961) 6:101–21.
67. Greenwood M. The Natural Duration of Cancer (Report on Public Health and Medical Subjects No. 33). London, UK: His Majesty’s Stationery Office (1926).
68. Parkin DM, Hakulinen T. Cancer Registration: Principles and Methods. Analysis of Survival. IARC Sci Publ (1991) 95:159–76.
69. Parmar MK, Torri V, Stewart L. Extracting Summary Statistics to Perform Meta-Analyses of the Published Literature for Survival Endpoints. Stat Med (1998) 17(24):2815–28. doi: 10.1002/(SICI)1097-0258(19981230)17:24<2815::AID-SIM110>3.0.CO;2-8
70. Höglund M, Sandin F, Hellström K, Björeman M, Björkholm M, Brune M, et al. Tyrosine Kinase Inhibitor Usage, Treatment Outcome, and Prognostic Scores in CML: Report From the Population-Based Swedish CML Registry. Blood (2013) 122(7):1284–92. doi: 10.1182/blood-2013-04-495598
71. Bower H, Björkholm M, Dickman PW, Höglund M, Lambert PC, Andersson TML. Life Expectancy of Patients With Chronic Myeloid Leukemia Approaches the Life Expectancy of the General Population. J Clin Oncol (2016) 34(24):2851–7. doi: 10.1200/JCO.2015.66.2866
72. Gunnarsson N, Sandin F, Höglund M, Stenke L, Björkholm M, Lambe M, et al. Population-Based Assessment of Chronic Myeloid Leukemia in Sweden: Striking Increase in Survival and Prevalence. Eur J Haematol (2016) 97(4):387–92. doi: 10.1111/ejh.12743
73. Smith AG, Painter D, Howell DA, Evans P, Smith G, Patmore R, et al. Determinants of Survival in Patients With Chronic Myeloid Leukaemia Treated in the New Era of Oral Therapy: Findings From a UK Population-Based Patient Cohort. BMJ Open (2014) 4(1):e004266. doi: 10.1136/bmjopen-2013-004266
74. Schmidt S, Wolf D, Thaler J, Burgstaller S, Linkesch W, Petzer A, et al. First Annual Report of the Austrian CML Registry. Wien Klin Wochenschr (2010) 122(19-20):558–66. doi: 10.1007/s00508-010-1450-x
75. Castagnetti F, Di Raimondo F, De Vivo A, et al. A Population-Based Study of Chronic Myeloid Leukemia Patients Treated With Imatinib in First Line. Am J Hematol (2017) 92(1):82–7. doi: 10.1002/ajh.24591
76. Daskalakis M, Feller A, Noetzli J, Bonadies N, Arndt V, Baerlocher GM, et al. Potential to Improve Therapy of Chronic Myeloid Leukemia (CML), Especially for Patients With Older Age: Incidence, Mortality, and Survival Rates of Patients With CML in Switzerland From 1995 to 2017. Cancers (2021) 13(24):6269. doi: 10.3390/cancers13246269
77. Faber E, Mužík J, Koza V, Demečková E, Voglová J, Demitrovičová L, et al. Treatment of Consecutive Patients With Chronic Myeloid Leukaemia in the Cooperating Centres From the Czech Republic and the Whole of Slovakia After 2000- a Report From the Population-Based CAMELIA Registry. Eur J Haematol (2011) 87(2):157–68. doi: 10.1111/j.1600-0609.2011.01637.x
78. Thielen N, Visser O, Ossenkoppele G, Janssen J. Chronic Myeloid Leukemia in the Netherlands: A Population-Based Study on Incidence, Treatment, and Survival in 3585 Patients From 1989 to 2012. Eur J Haematol (2016) 97(2):145–54. doi: 10.1111/ejh.12695
79. Nicolini FE, Alcazer V, Cony-Makhoul P, Heiblig M, Morisset S, Fossard G, et al. Long-Term Follow-Up of De Novo Chronic Phase Chronic Myelogenous Leukemia Patients on Front-Line Imatinib. Exp Hematol (2018) 64:97–105.e4. doi: 10.1016/j.exphem.2018.05.003
80. Penot A, Preux PM, Le Guyader S, Collignon A, Herry A, Dufour V, et al. Incidence of Chronic Myeloid Leukemia and Patient Survival: Results of Five French Population-Based Cancer Registries 1980-2009. Leuk Lymphoma (2015) 56(6):1771–7. doi: 10.3109/10428194.2014.974046
81. Hoffmann VS, Baccarani M, Hasford J, Castagnetti F, Di Raimondo F, Casado LF, et al. Treatment and Outcome of 2904 CML Patients From the EUTOS Population-Based Registry. Leukemia (2017) 31(3):593–601. doi: 10.1038/leu.2016.246
82. Chen Y, Wang H, Kantarjian H, Cortes J. Trends in Chronic Myeloid Leukemia Incidence and Survival in the United States From 1975 to 2009. Leuk Lymphoma (2013) 54(7):1411–7. doi: 10.3109/10428194.2012.745525
83. Brunner AM, Campigotto F, Sadrzadeh H, Drapkin BJ, Chen YB, Neuberg DS, et al. Trends in All-Cause Mortality Among Patients With Chronic Myeloid Leukemia: A Surveillance, Epidemiology, and End Results Database Analysis. Cancer (2013) 119(14):2620–9. doi: 10.1002/cncr.28106
84. Srour SA, Devesa SS, Morton LM, Check DP, Curtis RE, Linet MS, et al. Incidence and Patient Survival of Myeloproliferative Neoplasms and Myelodysplastic/Myeloproliferative Neoplasms in the United States, 2001-12. Br J Haematol (2016) 174(3):382–96. doi: 10.1111/bjh.14061
85. Al-Refaie WB, Vickers SM, Zhong W, Parsons H, Rothenberger D, Habermann EB, et al. Cancer Trials Versus the Real World in the United States. Ann Surg (2011) 254(3):438–43. doi: 10.1097/SLA.0b013e31822a7047
86. Murthy VH, Krumholz HM, Gross CP. Participation in Cancer Clinical Trials: Race-, Sex-, and Age-Based Disparities. JAMA (2004) 291(22):2720–6. doi: 10.1001/jama.291.22.2720
Keywords: cancer registries, chronic myeloid leukemia (CML), randomized controlled trials (RCTs), real-world data, survival, Europe, tyrosine kinase inhibitor (TKI), population-based studies
Citation: Vener C, Rossi S, Minicozzi P, Marcos-Gragera R, Poirel HA, Maynadié M, Troussard X, Pravettoni G, De Angelis R, Sant M and the EUROCARE-6 Working Group (2022) Clear Improvement in Real-World Chronic Myeloid Leukemia Survival: A Comparison With Randomized Controlled Trials. Front. Oncol. 12:892684. doi: 10.3389/fonc.2022.892684
Received: 09 March 2022; Accepted: 19 April 2022;
Published: 14 July 2022.
Edited by:
Mario Tiribelli, University of Udine, ItalyReviewed by:
Valentin Garcia-Gutierrez, Ramón y Cajal University Hospital, SpainAhmet Emre Eskazan, Istanbul University-Cerrahp
Copyright © 2022 Vener, Rossi, Minicozzi, Marcos-Gragera, Poirel, Maynadié, Troussard, Pravettoni, De Angelis, Sant and the EUROCARE-6 Working Group. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Claudia Vener, claudia.vener@unimi.it
†These authors share last authorship