Next Article in Journal
Non-Syndromic and Syndromic Defects in Children with Extracranial Germ Cell Tumors: Data of 2610 Children Registered with the German MAKEI 96/MAHO 98 Registry Compared to the General Population
Previous Article in Journal
Navigating Intraductal Papillary Mucinous Neoplasm Management through Fukuoka Consensus vs. European Evidence-Based Guidelines on Pancreatic Cystic Neoplasms—A Study on Two European Centers
Previous Article in Special Issue
Conditional Knockout of N-WASP Enhanced the Formation of Keratinizing Squamous Cell Carcinoma Induced by KRasG12D
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Cancers
Volume 16
Issue 11
10.3390/cancers16112158
cancers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Incidence and Relative Survival of Patients with Merkel Cell Carcinoma in North Rhine-Westphalia, Germany, 2008–2021

by
Andreas Stang
1,2,3,*,
Lennart Möller
3,
Ina Wellmann
3,
Kevin Claaßen
3,
Hiltraud Kajüter
3,
Selma Ugurel
4 and
Jürgen C. Becker
4,5,6,7
1
Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany
2
School of Public Health, Department of Epidemiology, Boston University, 715 Albany St, Boston, MA 02118, USA
3
Cancer Registry of North Rhine-Westphalia, Gesundheitscampus 10, 44801 Bochum, Germany
4
Department of Dermatology, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany
5
German Cancer Consortium (DKTK), Partner Site Essen/Düsseldorf, Hufelandstr. 55, 45147 Essen, Germany
6
Translational Skin Cancer Research, University Medicine Essen, Hufelandstr. 55, 45147 Essen, Germany
7
Faculty of Biology, University of Duisburg-Essen, Universitätsstrasse S05 T05 B24, 45117 Essen, Germany
*
Author to whom correspondence should be addressed.
Cancers 2024, 16(11), 2158; https://doi.org/10.3390/cancers16112158
Submission received: 17 May 2024 / Revised: 31 May 2024 / Accepted: 3 June 2024 / Published: 6 June 2024
(This article belongs to the Special Issue Skin Cancer: Risk Factors and Prevention)
Browse Figures
Versions Notes

Abstract

:

Simple Summary

Due to the rarity of Merkel cell carcinoma (MCC), only a few studies on both incidence and survival have been conducted. We provide up-to-date population-based incidence and relative survival estimates of MCC. We analyzed data from the cancer registry of North Rhine-Westphalia, Germany, for the years of 2008–2021, covering a population of 18 million individuals. We included all newly diagnosed MCC cases and calculated incidence rates and relative survival (observed divided by expected survival). Our analysis included 2164 MCC patients. The incidence of MCC was 5.2 and 3.8 per million for men and women, respectively. The 5-year relative survival was 59% in men and 71% in women. Survival was lower among men than women in all age–sex groups and was the highest for MCC of the upper extremity in both men and women. In terms of survival, the first two years are particularly critical.

Abstract

Background: To date, only a few population-representative studies have been carried out on the rare Merkel cell carcinoma (MCC). We provide incidence and survival estimates of MCC, including the conditional relative survival. Methods: We analyzed data from the cancer registry of North Rhine-Westphalia, Germany, 2008–2021, covering a population of 18 million. We included all newly diagnosed MCCs and calculated age-standardized (old European Standard population) incidence rates and unconditional and conditional relative survival. Results: Our analysis included 2164 MCC patients. The age-standardized incidence of MCC was 5.2 (men) and 3.8 (women) per million person-years. The 5-year relative survival was 58.8% (men) and 70.7% (women). Survival was lower among men than women in all age–sex groups and was highest for MCC of the upper extremity in both men (68.2%) and women (79.3%). The sex difference in survival is particularly due to the better survival of women with MCC of the head and neck. In terms of survival, the first two years are particularly critical. Conclusions: Our data validate the worse survival among men and highlights a more favorable prognosis for MCCs located on the limbs. The first two years after diagnosis of MCC are the years with the highest excess mortality.

1. Introduction

Merkel cell carcinoma (MCC) is a rare neuroendocrine cutaneous malignancy that was first described in 1972 [1]. MCC is highly aggressive, and patients with MCC have a considerably lower survival probability than patients with cutaneous melanoma. In a recent analysis of 1.4 million newly diagnosed skin cancer patients in England spanning 2013–2019, the 5-year overall survival probability was 80.2% for cutaneous malignant melanoma and 40.9% for Merkel cell carcinoma [2]. Risk factors for MCC are older age, immunosuppression, pre-existing hematologic neoplasms, chronic UV exposure, and thus a history of other cutaneous tumors. MCC can occur due to two distinct etiologies: virus-associated etiologies, caused by clonal integration of Merkel cell polyomavirus (MCPyV), or virus-negative driven etiologies, caused by UV-induced DNA mutations and damage [3].
Treating MCC typically involves a combination of therapies, depending on the stage and extent of the disease. Surgical excision is the standard treatment for localized MCC tumors. A wide local excision with clear margins together using a sentinel lymph node biopsy is recommended to remove the primary tumor and check if the cancer has spread to nearby lymph nodes. Radiation therapy targeting the tumor bed and the draining lymph node region is frequently used as an adjuvant treatment. More recently, adjuvant immunotherapy with immune checkpoint inhibitors (ICIs) has been shown to improve progression-free survival [4]. Moreover, ICIs have revolutionized the treatment landscape for advanced MCC. Indeed, immunotherapy has become the preferred first-line treatment for advanced MCC due to its improved efficacy and durability of responses compared with chemotherapy [5].
Several countries showed an increase in MCC incidence over time in non-Hispanic whites, and a latitude closer to the equator was found to be associated with MCC incidence in North American men, but only to a small extent in women, possibly due to occupational sun exposure patterns [6]. Due to the rarity of MCC, population-representative relative survival studies quantifying the excess mortality due to MCC and its therapeutic consequences are scarce [7]. Five-year relative survival estimates from population-based registries are available from a few populations, including the United States (1973–1999 and 1986–2004) [8,9], the Netherlands (1993–2007 and 1993–2015) [10,11], Finland (1983–2004) [12], Spain (1994–2002) [13], New Zealand (2000–2015) [14], Germany (2007–2011) [15], and Queensland (1993–2010) [16].
Here, we analyzed data from the cancer registry of North Rhine-Westphalia (NRW), Germany. A population-based cancer registry is able to validly determine the incidence and survival for a clearly defined population, whereas clinical registries of individual university hospitals do not have a clear population reference. However, population-based cancer registries often have the disadvantage that data on the clinical phenotype of the cancer and on details of the therapy as well as certain outcomes (e.g., progression-free survival, PFS) are only incompletely available.
The aim of this study was threefold. First, we provide the most recent population-based incidence rates of MCC. Second, we present population-based, up-to-date 5-year relative survival estimates by sex, age, and anatomic location. Third, in order to provide reliable data for the design and interpretation of adjuvant and neoadjuvant trials [4], we explore the conditional survival of MCC, that is, the survival of MCC patients who survived the first, second, third, and fourth year after diagnosis of MCC.

2. Material and Methods

The cancer registry of North Rhine-Westphalia (NRW) is one of the largest European population-based cancer registries, which covers 18 million people, of which 21% are older than 65 years and 11% are older than 75 years. Statewide cancer registration started in 2005.
Cancer reporting in NRW is mandatory and is empirically dominated by pathology reports. The estimated completeness of cancer registration overall is >90% since 2008 [17]. We extracted all incident primary Merkel cell carcinoma cases (International Classification of Diseases for Oncology, 3rd Edition (ICD-O) [18], M8247/3) registered by the Cancer Registry of NRW in the years 2008–2021. The vast majority of the 2164 cases were coded as MCC of the skin (ICD-O topography codes C44.0-C44.9) with the exception of n = 1 (external upper lip, C00.0), n = 1 (overlapping lesion of lip, C00.8), n = 1 (base of tongue, C01.9), n = 3 (parotid gland, C07.9), n = 1 (nasal cavity, C30.0), n = 1 (connective, subcutaneous and other soft tissue of lower limb and hip, C49.2), n = 1 (labium minus, C51.1), n = 2 (vulva, not other specified, C51.9), n = 1 (prepuce, penis, C60.0), n = 1 (glans penis, C60.1), n = 1 (scrotum, C63.2), and n = 3 (unknown primary site, C80.9). The low number of MCCs of unknown primary relates to the application of the ICD-O rules. The ICD-O rules, which are used worldwide in population-based cancer registries, stipulate that a reported morphology code M8247/3 (Merkel cell carcinoma) is assigned the topography C44 if a localization is missing unless another localization is explicitly reported.
We grouped the following anatomic locations: head and neck (C44.0-C44.4, C00.0, C00.8, C00.2, C01.9, C02.1, C07.9, C30.0), face and ears (C44.0-C44.3, C00.0, C00.8), scalp and neck (C44.4), trunk (C44.5), upper limb including shoulder (C44.6), lower limb including hip (C44.7, C49.2), genitals, overlapping, and unknown anatomic sites (C51.1, C51.9, C60.0, C60.1, C63.2, C44.8, C44.9, C80.9).
Patients with complete TNM (tumor, nodes, metastases) staging data were categorized according to the UICC (Union Internationale Contre le Cancer) as stages I–IV [19]. If information on T, N, or M stage was missing, a categorization into at least UICC I–II or UICC III–IV was performed from the available information if possible. For example, if a tumor was only known to be N0 and M0 with a missing T-stage, this tumor was classified as UICC I–II. If it was only known that a tumor was N+ (i.e., N1-N3) with a missing M-stage, this tumor was classified as UICC III–IV.

Statistical Methods

Through the use of the annual population figures by age and sex, we calculated age-specific and age-standardized incidence rates for the overall registration period by sex. We used the “old” European Standard Population [20] for the age standardization of incidence rates. For future comparisons of incidence rates in Germany with other countries, we also provide age-standardized incidence rates, standardized with the world standard population and the U.S. 2000 standard population, in the Supplementary Materials.
We calculated the relative survival, which is defined as the ratio of the observed probability of survival and the expected probability of survival. In principle, the observed survival probability by Kaplan–Meier estimation in a calendar year of an age and sex group is divided by the expected survival probability in that calendar year generated from the general population life table for the same age and sex group [21]. A relative survival probability below 100% indicates excess mortality due to the cancer or its sequelae. The advantage of relative survival compared with disease-specific survival is that the cause of death (death certificates), which is often incorrectly stated, is not required for relative survival. For the 5-year cumulative survival probability, the five annual relative survival probabilities are multiplied together [22]. Survival estimates were calculated with the R package periodR [23]. The cancer registry obtains information on vital status through record linkage with all death certificates of people in North Rhine-Westphalia. The last complete linkage was carried out as of 31 December 2021. This date was used as the closing data for the follow-up. We also estimated conditional relative survival of patients who survived the first, second, third, and fourth year after diagnosis of MCC. We stratified survival estimates by sex, age (<65, 65–74, 75–84, 85+ years), and topography.
A period analysis methodology was employed to derive the most up-to-date relative survival estimates [24,25,26]. The period analysis approach used available survival observations during the calendar period of 2017–2021 of the patients diagnosed during 2012–2021 (i.e., in addition to those diagnosed in the period of 2017–2021). Patients who survived until 2017 contributed (left truncated) survival experience to the analysis as well. Supplementary Figure S1 illustrates the data usage.
Due to missing data on stage (UICC), we performed multiple imputation using the assumption of missing at random to replace missing values. Statistical details of the multiple imputation can be found in the Supplementary Materials. We calculate and report the standard errors (SE) or 95% confidence intervals (95%CIs) to assess the precision of our estimates, as our goal is estimation and not significance testing. We wish to avoid publication bias by preferential reporting of significant results. Instead, we judge the value of our estimates by their precision and validity [27,28].
For the study of the association between sex and overall survival and disease-specific survival, we ran Cox proportional hazards regression models and used different degrees of adjustment. The first model only included sex. The second model additionally included age and topography. The third model additionally included age, topography, and UICC stage. We included these adjustment variables because they were associated with sex and were predictors of the outcome. In the complete case analysis, the proportional hazards assumption was checked by Schoenfeld residuals [29]. The proportional hazards assumption was not violated.

3. Results

During the period of 2008–2021, a total of 2164 patients (1049 men, 1115 women) with newly diagnosed MCC were registered. Tumors were found in the following localizations: head and neck, 891 cases (41%); trunk, 177 cases (8%); upper limb, 512 cases (24%); lower limb, 297 cases (14%); and other, unspecified locations, or genital skin, 287 cases (13%). The median age at diagnosis was 77 years (25th percentile [P25]: 70, 75th percentile [P75]: 82 years) and 79 years (P25: 72, P75: 85 years) among men and women, respectively. The age-standardized incidence rate of MCC during 2008–2021 was 5.2 and 3.8 per million person-years for men and women, respectively. This means that the age-standardized incidence rate is 35.3% (95%CI 23.5–48.2%) higher for men than for women. The age-specific incidence rates were higher for men in each age group. The age-standardized incidence rate of MCC was highest in the skin of the head and neck among both men and women (Table 1 and Table S1).
Because the UICC tumor staging is based on clinical parameters (e.g., tumor diameter), which are sometimes collected only during the course (e.g., status of the sentinel lymph node), and because the registration of incident Merkel cell carcinoma cases is based primarily on reports from pathologists, the UICC tumor stage was missing in 59% and 62% of male and female cases, respectively. A higher proportion of missing UICC values was associated with older age at diagnosis, localization (especially missing localization and skin of the genitals), early years of diagnosis, and patient death, especially deaths not attributable to MCC (e.g., death due to myocardial infarction, etc.) (Table S2).
In the 854 patients for which the UICC stage was reported, the stage distribution for males and females was as follows: stage I—43.1% and 50.8%, stage II—11.2% and 12.0%, stage I/II—4.7% and 4.5%, stage III—21.2% and 17.9%, stage IV—12.8% and 8.0%, and stage III/IV—7.0% and 6.8%, respectively. Even after multiple imputation, men had a less favorable UICC stage distribution than women (Figure 1).
The 5-year relative survival (5yr-RS) was 58.8% in men (95%CI 52.3–65.4%) and 70.7% in women (95%CI 64.2–77.3%). The 5yr-RS was markedly lower in men than in women in each age stratum (<65, 65–74, 75–84, 85+ years). The 5yr-RS for head and neck MCC was 54.0% (95%CI: 41.8–66.1%) and 72.5% (95%CI: 62.4–82.6%) in men and women, respectively. The 5yr-RS was highest for MCC of the arms in women (79.3%, 95%CI 65.8–92.8%) and men (68.2%, 95%CI 55.8–80.6%) (Table 2). Both the complete case survival analysis, which had only patients without missing data for UICC, and the survival analysis, which was carried out after multiple imputation, showed that, after adjustment for age, topography, and UICC, men still had a less favorable prognosis (overall mortality and disease-specific mortality) than women (Table 3).
Unconditional relative survival, which is determined from the time of diagnosis, shows the sharpest drop of relative survival probability for both sexes within the first year after diagnosis (men: −13.0 percentage points; women: −12.7 percentage points). Even in the second year after diagnosis, there is still a marked drop in the relative survival probability, particularly for men (men: −13.2 percentage points; women: −6.9 percentage points). In the following years, the percentage point drops are markedly lower. This is also shown by the analyses of conditional relative survival, in which survival is only determined from the first, second, third and fourth year after diagnosis of MCC (Figure 2, Tables S3 and S4).

4. Discussion

The age-standardized incidence of MCC was 35.3% higher in men than in women. Each age group showed a higher incidence rate in men than in women. MCC of the skin of the head and neck was predominant in both men and women. The 5-year relative survival of MCC overall and in each age group was lower in men than it was in women. When comparing 5-year relative survival by anatomic location, it appears that the overall difference in survival from MCC between men and women is primarily due to differences in survival from MCC of the skin of the head and neck. It has previously been reported that the conditional survival of MCC patients is dynamic and increases with time since the initial diagnosis [30]. Our data confirm that the probability of survival after MCC diagnosis is most reduced in the first two years after diagnosis, and each additional year after diagnosis of MCC that is survived improves the probability of survival. This finding is important for the design and interpretation of adjuvant and neo-adjuvant therapeutic trials in MCC.
International comparisons of MCC incidence rates are complicated by differences in registration and evaluation methods, particularly the choice of age standard. A comparison of age-standardized rates (old European standard) in North Rhine-Westphalia, Germany (men: 5.2 per million person-years; women: 3.8 per million person-years), with France in 2006–2010 (men: 4.3 per million person-years; women 3.9 per million person-years) [31] and the Netherlands in 2016 (men: 6.7 per million person-years; women: 5.2 per million person-years) [11] shows that incidence rates are very similar in these countries, which mainly consist of non-Hispanic white populations and live at similar latitudes.
In our analyses, the 5yr-RS of men with MCC was 11.9% lower than that of women in our analyses. This is in line with other registry-based studies that reported 5yr-RS by sex. There was always a clear difference in survival to the detriment of men, including the Netherlands [10], Finland [12], Queensland [16], and Germany [15]—the only exception was one report from New Zealand [14]. To further investigate this sex effect, the authors of three of these papers examined the association between sex and survival using regression models adjusting for stage distribution, age, and anatomic site [11,14,16]. In all three studies, the sex effect persisted after adjustment, suggesting that regardless of the stage of MCC at diagnosis, men have a worse prognosis than women. Our multiple imputation analysis of observed overall and disease-specific survival that adjusted for age, anatomic location, and UICC stage corroborated this finding.
The sex difference in cancer survival have been reported before. Indeed, both incidence and survival of cancer vary markedly by sex, with males generally having lower survival compared with females. A pan-cancer analysis using data from the SEER program of 2001 to 2016 found that male-to-female survival differences were noted across various cancer types, races, and age groups [32]. A Swedish cohort study also reported that male sex is associated with increased risk and poorer survival for most cancer sites. Our findings add to the evidence that the fundamental biology of sex differences affects cancers of all types [33].
Two previous studies reported that the 5yr-RS in MCC is highest in the face or ears [14,16]. Neither of these two studies reported this finding in a sex-specific manner. Our sex-specific analyses showed that the 5yr-RS for MCC of the face or ears is high only in women (72.5%), while it is markedly lower in men (57.5%). We found the highest 5yr-RS for MCC of the upper limbs in both sexes.
In a recent publication, McEvoy et al. described one of the largest MCC cohorts of a university tertiary center for MCC in terms of clinical outcome and also provided a review of the published literature. In their cohort of 618 patients, they described an overall 5-year recurrence probability of 40% for all stages, with the majority of recurrences occurring within the first 2 years and 95% of recurrences occurring within the first 3 years [34]. Miura et al. found that the most critical interval in terms of survival of advanced-stage MCCs are the first two years after diagnosis [35]. We corroborated this finding through our detailed unconditional and conditional relative survival analysis of patients who survived the first, second, third, and fourth year after diagnosis of MCC.
Although we used a large data set of 2164 MCC patients, several limitations of our results exist. First, due to missing values for UICC stage, we had to use multiple imputation to replace missing values in order to adjust for the potentially confounding effect of tumor stage at initial diagnosis. Second, the important risk and prognosis factor of immunosuppression (e.g., due to hematologic neoplasia, HIV infection, or organ transplantation) is not available in the routine data of the cancer registries in Germany and could not be examined in detail [36]. Third, further morphological subtyping of MCC or establishing the MCPyV status was not possible as this would have required the detailed clinical description, detailed pathology findings, and additional molecular characterization of the specimens. While population-based cancer registries focus on epidemiologic measures of cancer, i.e., cancer incidence, its distribution by age, sex, and location of patients, and survival, specialized disease registries typically focus on very detailed phenotyping, including molecular pathology, precise treatment protocols including first-line, second-line, etc., detailed follow-up endpoints including progression, recurrence, and also patient-reported outcomes. The disadvantage of specialized disease registries, however, is often the lack of a clear population reference that would allow for the calculation of epidemiologic measures. Thus, in order to better combine both approaches, the German Cancer Early Detection and Registry Act (KFRG) came into force on 9 April 2013. While full implementation in all German states will require some time to establish the appropriate structures, a comparison of figures between specialized disease registries and population-based cancer registries over the last few years already shows the positive development, so that evaluations will soon be possible. Future high-resolution studies, i.e., in registries that also collect tissue samples, that allow for further biological subtyping of MCC and have detailed staging information may provide further insight into the differential prognosis of MCC in men and women.

5. Conclusions

Our data of a population-representative cancer registry not only provide up-to-date incidence and survival data for MCC and validate worse survival among men, but also highlight a more favorable prognosis for MCCs located on the limbs. Most crucially, however, we showed that the first two years after diagnosis of MCC are the years with the highest excess mortality of MCC patients. The latter is highly relevant for the design and interpretation of adjuvant and neo-adjuvant therapeutic trials in MCC.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers16112158/s1, Figure S1: Data use for estimation of 5-year survival by period analysis for the calendar period 2017–2021 (solid frame, the numbers within the cells indicate the follow-up years after diagnosis that may be observed in the respective calendar year of follow-up); Table S1: Crude and age-standardized incidence rate (cases per million person-years) of Merkel cell carcinoma among men and women in North Rhine-Westphalia, Germany, 2008–2021; Table S2: Potential determinants of missing UICC stages among patients with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2008–2021; Table S3: Unconditional and conditional relative survival (%) among men and women with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2017–2021; Table S4: Absolute decline of survival (percentage points) from year to year among men and women with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2017–2021. References [37,38,39] are cited in the Supplementary Materials.

Author Contributions

A.S.: conceptualized the study, supervised the data analysis, and wrote the original and final draft; L.M.: performed the data curation and formal statistical analysis and reviewed the draft; I.W.: performed the data curation and formal statistical analysis and reviewed the draft; H.K.: supervised the data analysis and reviewed the draft; K.C., S.U. and J.C.B.: conceptualized the study and reviewed the draft. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

According to German law, an ethical review by an ethics committee is not required for cancer registry data analysis projects.

Informed Consent Statement

Under German law, a patient consent was not required for this project.

Data Availability Statement

The data can be requested from the Cancer Registry of North Rhine-Westphalia.

Acknowledgments

We would like to thank Johannes Hüsing, Cancer Registry of North Rhine-Westphalia, for the supervision of the multiple imputation subproject.

Conflicts of Interest

A.S.: L.M., I.W., H.K., and K.C. do not report any conflicts of interest. S.U. declares research support from Bristol Myers Squibb and Merck Serono; speakers and advisory board honoraria from Bristol Myers Squibb, Merck Sharp & Dohme, Merck Serono, and Novartis; and meeting and travel support from Almirall, Bristol Myers Squibb, IGEA Clinical Biophysics, Merck Sharp & Dohme, Novartis, Pierre Fabre, and Sun Pharma, outside of the submitted work. J.C.B.: Speaker’s bureau honoraria from Amgen, MerckSerono, Pfizer, Recordati, and Sanofi; paid consultant/advisory/DSMB board member for Almirall, Boehringer Ingelheim, ICON, InProTher, Pfizer, 4SC, and Sanofi/Regeneron; and research grants from Bristol Myers Squibb, Merck Serono, HTG, IQVIA, and Alcedis.

References

  1. Toker, C. Trabecular carcinoma of the skin. Arch. Dermatol. 1972, 105, 107–110. [Google Scholar] [CrossRef] [PubMed]
  2. van Bodegraven, B.; Vernon, S.; Eversfield, C.; Board, R.; Craig, P.; Gran, S.; Harwood, C.A.; Keohane, S.; Levell, N.J.; Matin, R.N.; et al. ‘Get data out’ skin: National cancer registry incidence and survival rates for all registered skin tumour groups for 2013–2019 in england. Br. J. Dermatol. 2023, 188, 777–784. [Google Scholar] [CrossRef]
  3. Becker, J.C.; Stang, A.; DeCaprio, J.A.; Cerroni, L.; Lebbe, C.; Veness, A.; Nghiem, P. Merkel cell carcinoma. Nat. Rev. Dis. Primers 2017, 3, 17077. [Google Scholar] [CrossRef] [PubMed]
  4. Becker, J.C.; Ugurel, S.; Leiter, U.; Meier, F.; Gutzmer, R.; Haferkamp, S.; Zimmer, L.; Livingstone, E.; Eigentler, T.K.; Hauschild, A.; et al. Adjuvant immunotherapy with nivolumab versus observation in completely resected merkel cell carcinoma (admec-o): Disease-free survival results from a randomised, open-label, phase 2 trial. Lancet 2023, 402, 798–808. [Google Scholar] [CrossRef] [PubMed]
  5. Becker, J.C.; Stang, A.; Schrama, D.; Ugurel, S. Merkel cell carcinoma: Integrating epidemiology, immunology, and therapeutic updates. Am. J. Clin. Dermatol. 2024. [Google Scholar] [CrossRef] [PubMed]
  6. Stang, A.; Becker, J.C.; Nghiem, P.; Ferlay, J. The association between geographic location and incidence of merkel cell carcinoma in comparison to melanoma: An international assessment. Eur. J. Cancer 2018, 94, 47–60. [Google Scholar] [CrossRef] [PubMed]
  7. Mohsen, S.T.; Price, E.L.; Chan, A.W.; Hanna, T.P.; Limacher, J.J.; Nessim, C.; Shiers, J.E.; Tron, V.; Wright, F.C.; Drucker, A.M. Incidence, mortality and survival of merkel cell carcinoma: A systematic review of population-based studies. Br. J. Dermatol. 2024, 190, 811–824. [Google Scholar] [CrossRef] [PubMed]
  8. Agelli, M.; Clegg, L.X. Epidemiology of primary merkel cell carcinoma in the united states. J. Am. Acad. Dermatol. 2003, 49, 832–841. [Google Scholar] [CrossRef] [PubMed]
  9. Lemos, B.D.; Storer, B.E.; Iyer, J.G.; Phillips, J.L.; Bichakjian, C.K.; Fang, L.C.; Johnson, T.M.; Liegeois-Kwon, N.J.; Otley, C.C.; Paulson, K.G.; et al. Pathologic nodal evaluation improves prognostic accuracy in merkel cell carcinoma: Analysis of 5823 cases as the basis of the first consensus staging system. J. Am. Acad. Dermatol. 2010, 63, 751–761. [Google Scholar] [CrossRef]
  10. Reichgelt, B.A.; Visser, O. Epidemiology and survival of merkel cell carcinoma in the netherlands. A population-based study of 808 cases in 1993–2007. Eur. J. Cancer 2011, 47, 579–585. [Google Scholar] [CrossRef]
  11. Uitentuis, S.E.; Louwman, M.W.J.; van Akkooi, A.C.J.; Bekkenk, M.W. Treatment and survival of merkel cell carcinoma since 1993: A population-based cohort study in the netherlands. J. Am. Acad. Dermatol. 2019, 81, 977–983. [Google Scholar] [CrossRef]
  12. Kukko, H.; Bohling, T.; Koljonen, V.; Tukiainen, E.; Haglund, C.; Pokhrel, A.; Sankila, R.; Pukkala, E. Merkel cell carcinoma—A population-based epidemiological study in finland with a clinical series of 181 cases. Eur. J. Cancer 2012, 48, 737–742. [Google Scholar] [CrossRef] [PubMed]
  13. Rubio-Casadevall, J.; Hernandez-Pujol, A.M.; Ferreira-Santos, M.C.; Morey-Esteve, G.; Vilardell, L.; Osca-Gelis, G.; Vilar-Coromina, N.; Marcos-Gragera, R. Trends in incidence and survival analysis in non-melanoma skin cancer from 1994 to 2012 in girona, spain: A population-based study. Cancer Epidemiol. 2016, 45, 6–10. [Google Scholar] [CrossRef]
  14. Lee, Y.; Chao, P.; Coomarasamy, C.; Mathy, J.A. Epidemiology and survival of merkel cell carcinoma in new zealand: A population-based study between 2000 and 2015 with international comparison. Australas J. Dermatol. 2019, 60, e284–e291. [Google Scholar] [CrossRef]
  15. Eisemann, N.; Jansen, L.; Castro, F.A.; Chen, T.; Eberle, A.; Nennecke, A.; Zeissig, S.R.; Brenner, H.; Katalinic, A.; GEKID Cancer Survival Working Group. Survival with nonmelanoma skin cancer in germany. Br. J. Dermatol. 2016, 174, 778–785. [Google Scholar] [CrossRef]
  16. Youlden, D.R.; Soyer, H.P.; Youl, P.H.; Fritschi, L.; Baade, P.D. Incidence and survival for merkel cell carcinoma in queensland, australia, 1993–2010. JAMA Dermatol. 2014, 150, 864–872. [Google Scholar] [CrossRef]
  17. Koch-Institut, R. Krebs in Deutschland 2007/2008; Robert Koch-Institut: Berlin, Germany, 2012. [Google Scholar]
  18. Fritz, A.; Percy, C.; Jack, A.; Shanmugaratnam, K.; Sobin, L.; Parkin, D.L.; Whelan, S. International Classification of Diseases for Oncology, 3rd ed.; World Health Organization: Geneva, Switzerland, 2000. [Google Scholar]
  19. Brierley, J.D.; Gospodarowicz, M.; Wittekind, C. Tnm Classification of Malignant Tumours, 8th ed.; Wiley-Blackwell: Chichester, UK, 2016; p. 272. [Google Scholar]
  20. Doll, R.; Cook, P. Summarizing indices for comparison of cancer incidence data. Int. J. Cancer 1967, 2, 269–279. [Google Scholar] [CrossRef]
  21. Berkson, J.; Gage, R.P. Calculation of survival rates for cancer. Proc. Staff. Meet. Mayo Clin. 1950, 25, 270–286. [Google Scholar]
  22. Ederer, F.; Axtell, L.M.; Cutler, S.J. The relative survival rate: A statistical methodology. Natl. Cancer Inst. Monogr. 1961, 6, 101–121. [Google Scholar] [PubMed]
  23. Holleczek, B.; Gondos, A.; Brenner, H. Periodr—An r package to calculate long-term cancer survival estimates using period analysis. Methods Inf. Med. 2009, 48, 123–128. [Google Scholar] [CrossRef]
  24. Brenner, H.; Gefeller, O. An alternative approach to monitoring cancer patient survival. Cancer 1996, 78, 2004–2010. [Google Scholar] [CrossRef]
  25. Brenner, H.; Soderman, B.; Hakulinen, T. Use of period analysis for providing more up-to-date estimates of long-term survival rates: Empirical evaluation among 370,000 cancer patients in finland. Int. J. Epidemiol. 2002, 31, 456–462. [Google Scholar] [CrossRef] [PubMed]
  26. Talback, M.; Stenbeck, M.; Rosen, M. Up-to-date long-term survival of cancer patients: An evaluation of period analysis on swedish cancer registry data. Eur. J. Cancer 2004, 40, 1361–1372. [Google Scholar] [CrossRef] [PubMed]
  27. Sterne, J.A.; Davey, S.G. Sifting the evidence-what’s wrong with significance tests? BMJ 2001, 322, 226–231. [Google Scholar] [CrossRef] [PubMed]
  28. Lash, T.L. Heuristic thinking and inference from observational epidemiology. Epidemiology 2007, 18, 67–72. [Google Scholar] [CrossRef] [PubMed]
  29. Schoenfeld, D. Partial residuals for the proportional hazards regression model. Biometrika 1982, 69, 239–241. [Google Scholar] [CrossRef]
  30. Zhang, J.; Xiang, Y.; Chen, J.; Liu, L.; Jin, J.; Zhu, S. Conditional survival analysis and dynamic prediction of long-term survival in merkel cell carcinoma patients. Front. Med. 2024, 11, 1354439. [Google Scholar] [CrossRef]
  31. Fondain, M.; Dereure, O.; Uhry, Z.; Guizard, A.V.; Woronoff, A.S.; Colonna, M.; Molinie, F.; Bara, S.; Velten, M.; Marrer, E.; et al. Merkel cell carcinoma in france: A registries-based, comprehensive epidemiological survey. J. Eur. Acad. Dermatol. Venereol. 2018, 32, 1292–1296. [Google Scholar] [CrossRef] [PubMed]
  32. Dong, M.; Cioffi, G.; Wang, J.; Waite, K.A.; Ostrom, Q.T.; Kruchko, C.; Lathia, J.D.; Rubin, J.B.; Berens, M.E.; Connor, J.; et al. Sex differences in cancer incidence and survival: A pan-cancer analysis. Cancer Epidemiol. Biomark. Prev. 2020, 29, 1389–1397. [Google Scholar] [CrossRef]
  33. Radkiewicz, C.; AJohansson, L.V.; Dickman, P.W.; Lambe, M.; Edgren, G. Sex differences in cancer risk and survival: A swedish cohort study. Eur. J. Cancer 2017, 84, 130–140. [Google Scholar] [CrossRef]
  34. McEvoy, A.M.; Lachance, K.; Hippe, D.S.; Cahill, K.; Moshiri, Y.; Lewis, C.W.; Singh, N.; Park, S.Y.; Thuesmunn, Z.; Cook, M.M.; et al. Recurrence and mortality risk of merkel cell carcinoma by cancer stage and time from diagnosis. JAMA Dermatol. 2022, 158, 382–389. [Google Scholar] [CrossRef] [PubMed]
  35. Miura, J.T.; Lindner, H.; Karakousis, G.C.; Sharon, C.E.; Gimotty, P.A. Conditional survival estimates for merkel cell carcinoma reveal the dynamic nature of prognostication. J. Surg. Oncol. 2022, 126, 348–355. [Google Scholar] [CrossRef] [PubMed]
  36. Mistry, K.; Levell, N.J.; Hollestein, L.; Wakkee, M.; Nijsten, T.; Knott, C.S.; Steven, N.M.; Craig, P.J.; Venables, Z.C. Trends in incidence, treatment and survival of merkel cell carcinoma in england 2004–2018: A cohort study. Br. J. Dermatol. 2023, 188, 228–236. [Google Scholar] [CrossRef] [PubMed]
  37. Rubin, D.B. Multiple Imputation for Nonresponse in Surveys; Wiley: New York, NY, USA, 1987. [Google Scholar]
  38. Sterne, J.A.C. Multiple imputation for missing data in epidemiological and clinical research: Potential and pitfalls. BMJ 2009, 338, b2393. [Google Scholar] [CrossRef]
  39. White, I.R.; Royston, P. Imputing missing covariate values for the Cox model. Stat. Med. 2009, 28, 1982–1998. [Google Scholar] [CrossRef]
Cancers 16 02158 g001
Figure 1. Distribution of UICC stages among 2164 patients with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2008–2021, before and after multiple imputation. CC: Stage distribution according to complete case analysis; percentage distribution only among cases with UICC staging information. MI: Stage distribution after multiple imputation of missing data.
Figure 1. Distribution of UICC stages among 2164 patients with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2008–2021, before and after multiple imputation. CC: Stage distribution according to complete case analysis; percentage distribution only among cases with UICC staging information. MI: Stage distribution after multiple imputation of missing data.
Cancers 16 02158 g001
Cancers 16 02158 g002
Figure 2. Unconditional and conditional relative survival (%) among men and women with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2017–2021. Legend for Figure 1: Unconditional relative survival (period approach) starts at year zero of follow-up. Conditional relative survival starts after 1, 2, 3, and 4 years, respectively.
Figure 2. Unconditional and conditional relative survival (%) among men and women with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2017–2021. Legend for Figure 1: Unconditional relative survival (period approach) starts at year zero of follow-up. Conditional relative survival starts after 1, 2, 3, and 4 years, respectively.
Cancers 16 02158 g002
Table 1. Age-standardized incidence rate (cases per million person-years) of Merkel cell carcinoma among men and women in North Rhine-Westphalia, Germany, 2008–2021.
Table 1. Age-standardized incidence rate (cases per million person-years) of Merkel cell carcinoma among men and women in North Rhine-Westphalia, Germany, 2008–2021.
CharacteristicMenWomen
NRateSENRateSE
Overall10495.20.1611153.80.13
Localization
 Head3611.70.095301.60.07
  Face/Ear2741.20.084861.50.07
  Scalp/Neck850.40.04410.10.02
 Trunk1140.60.06630.30.04
 Upper limb2761.40.092360.90.06
 Lower limb1440.80.061530.60.05
 Other1540.80.061330.50.05
Age at diagnosis (years)
 <651351.00.091140.90.08
 65–7428823.11.3723116.21.08
 75–8444554.72.6246640.51.92
 85+18196.17.1430468.43.92
UICC stages 1N% N%
 Non-missing429 425
  I18543.1 21650.8
  II4811.2 5112.0
  III9121.2 7617.9
  IV5512.8 348.0
  I–II204.7 194.5
  III–IV307.0 296.8
 Missing620 690
Rates are standardized by the “old” European standard population. SE: Standard error of the rate; 1 incidence rates for stages are not presented because of missing data.
Table 2. Five-year relative survival (%) of the years 2017–2021 among men and women with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany.
Table 2. Five-year relative survival (%) of the years 2017–2021 among men and women with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany.
CharacteristicMenWomen
Patients (N)Point Estimate %95%CIPatients (N)Point Estimate %95%CI
Overall68658.8[52.3;65.4]70070.7[64.2;77.3]
Localization
 Head and neck23354.0[41.8;66.1]35072.5[62.4;82.6]
  Face/Ear17957.5[43.5;71.5]31973.8[63.2;84.4]
  Scalp/Neck5243.2[18.8;67.5]2959.7[26.6;92.8]
 Trunk7854.4[36.3;72.5]4245.6[24.3;67.0]
 Upper limb19068.2[55.8;80.6]14279.3[65.8;92.8]
 Lower limb10662.9[46.4;79.3]10675.9[60.9;90.9]
 Other7948.1[30.6;65.5]6049.8[30.0;69.7]
Age at diagnosis (years)
 <659565.8[51.6;80.0]7378.4[65.2;91.6]
 65–7417962.3[51.5;73.0]15281.7[71.2;92.2]
 75–8429756.4[46.0;66.8]29569.8[60.3;79.3]
 85+11552.2[28.7;75.8]18057.0[39.3;74.7]
Point estimate: estimated 5-year relative survival by period approach in percentages; 95%CI: 95% confidence interval.
Table 3. Effect of sex on survival among patients with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2008–2021.
Table 3. Effect of sex on survival among patients with newly diagnosed Merkel cell carcinoma in North Rhine-Westphalia, Germany, 2008–2021.
ModelCohortAdjustment SetHazard Ratio95%CI
Overall mortality
#1Complete cases (n = 854) 1Empty0.670.54–0.83
#2Complete cases (n = 854) 1Age, topography0.580.46–0.72
#3Complete cases (n = 854) 1Age, topography, UICC0.590.47–0.74
#4Overall cohort (n = 2164)Age, topography, UICC0.690.61–0.78
Disease-specific mortality
#5Complete cases (n = 854) 1Empty0.580.40–0.83
#6Complete cases (n = 854) 1Age, topography0.530.37–0.78
#7Complete cases (n = 854) 1Age, topography, UICC0.550.38–0.81
#8Overall cohort (n = 2164)Age, topography, UICC0.690.54–0.89
1 Complete cases (n = 854 cases) are a subset of the overall cohort with zero missing items regarding year, sex, topography, age at diagnosis, and UICC stage; the overall cohort (n = 2164) has zero missing items for these items after multiple imputation.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Stang, A.; Möller, L.; Wellmann, I.; Claaßen, K.; Kajüter, H.; Ugurel, S.; Becker, J.C. Incidence and Relative Survival of Patients with Merkel Cell Carcinoma in North Rhine-Westphalia, Germany, 2008–2021. Cancers 2024, 16, 2158. https://doi.org/10.3390/cancers16112158

AMA Style

Stang A, Möller L, Wellmann I, Claaßen K, Kajüter H, Ugurel S, Becker JC. Incidence and Relative Survival of Patients with Merkel Cell Carcinoma in North Rhine-Westphalia, Germany, 2008–2021. Cancers. 2024; 16(11):2158. https://doi.org/10.3390/cancers16112158

Chicago/Turabian Style

Stang, Andreas, Lennart Möller, Ina Wellmann, Kevin Claaßen, Hiltraud Kajüter, Selma Ugurel, and Jürgen C. Becker. 2024. "Incidence and Relative Survival of Patients with Merkel Cell Carcinoma in North Rhine-Westphalia, Germany, 2008–2021" Cancers 16, no. 11: 2158. https://doi.org/10.3390/cancers16112158

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop