Skip to main content

Main menu

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Editorial Policies
    • Subscribers
    • Advertisers
    • Editorial Board
    • Special Issues 2025
  • Journal Metrics
  • Other Publications
    • In Vivo
    • Cancer Genomics & Proteomics
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
    • 2008 Nobel Laureates
  • About Us
    • General Policy
    • Contact
  • Other Publications
    • Anticancer Research
    • In Vivo
    • Cancer Genomics & Proteomics

User menu

  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Anticancer Research
  • Other Publications
    • Anticancer Research
    • In Vivo
    • Cancer Genomics & Proteomics
  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Anticancer Research

Advanced Search

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Editorial Policies
    • Subscribers
    • Advertisers
    • Editorial Board
    • Special Issues 2025
  • Journal Metrics
  • Other Publications
    • In Vivo
    • Cancer Genomics & Proteomics
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
    • 2008 Nobel Laureates
  • About Us
    • General Policy
    • Contact
  • Visit us on Facebook
  • Follow us on Linkedin
Research ArticleClinical Studies
Open Access

Impact of Surgery Refusal on Overall Survival in Merkel Cell Carcinoma

KYLE POPP, REED POPP, JADE BOWERS, SYEDA HOORULAIN AHMED, RAMIN SHEKOUHI, SHIVAM BANSAL, SEEMA SHARAN, HARSHEEN K. MANAISE, BANSI P. SAVALIY, SWATHI R. RAIKOT, PAOLA BERRIOS JIMENEZ, FATIMA MUBARAK, ESINAM P. EKPEH, KULKAEW B. SUKNIAM, GABRIELLE KOWKABANY, ANGEL AGUAYO and EMMANUEL M. GABRIEL
Anticancer Research June 2025, 45 (6) 2443-2451; DOI: https://doi.org/10.21873/anticanres.17615
KYLE POPP
1University of Florida, Gainesville, FL, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: Kylelpopp@gmail.com
REED POPP
2University of Florida College of Medicine, Gainesville, FL, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
JADE BOWERS
3Florida State University College of Medicine, Tallahassee, FL, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SYEDA HOORULAIN AHMED
4Division of Plastic and Reconstructive Surgery, Department of Surgery, University of Florida, Gainesville, FL, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
RAMIN SHEKOUHI
4Division of Plastic and Reconstructive Surgery, Department of Surgery, University of Florida, Gainesville, FL, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SHIVAM BANSAL
5Government Medical College & Hospital, Chandigarh, India;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SEEMA SHARAN
5Government Medical College & Hospital, Chandigarh, India;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
HARSHEEN K. MANAISE
5Government Medical College & Hospital, Chandigarh, India;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
BANSI P. SAVALIY
6Mayo Clinic, Rochester, MN, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SWATHI R. RAIKOT
7Emory University School of Medicine, Atlanta, GA, U.SA.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
PAOLA BERRIOS JIMENEZ
8University of Puerto Rico School of Medicine, San Juan, Puerto Rico;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
FATIMA MUBARAK
9Aga Khan University, Karachi, Pakistan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
ESINAM P. EKPEH
10University of North Florida, Jacksonville, FL, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
KULKAEW B. SUKNIAM
11Duke University Medical Center, Durham, NC, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
GABRIELLE KOWKABANY
12The University of Alabama, Tuscaloosa, AL, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
ANGEL AGUAYO
13University of Puerto Rico School of Medicine, Medical Sciences Campus, San Juan, U.S.A.;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
EMMANUEL M. GABRIEL
14Division of Surgical Oncology, Department of General Surgery, Mayo Clinic, Jacksonville, FL, U.S.A.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Background/Aim: The mainstay of treatment for Merkel cell carcinoma (MCC) is surgery; however, some individuals refuse this treatment modality, which may influence their survival outcomes. Interventions to increase acceptance of suggested care could be informed by an understanding of the factors linked to surgery refusal.

Patients and Methods: This retrospective study used data on patients with MCC from the National Cancer Database from 2004 to 2019 to assess the effect of surgical refusal on overall survival (OS) and identify related clinical and demographic characteristics. The Kaplan–Meier method was used to examine OS, and the log-rank test was used to compare survival curves. Wilcoxon Rank Sum or Pearson Chi-square tests were used to examine patient characteristics.

Results: Of the 9,901 patients with MCC who were advised to undergo surgery, 9,863 (99.6%) underwent surgery, while 38 (0.4%) refused. Patients who refused surgery were older (mean age 74.3 years vs. 82.6 years), in a later stage of disease (54% of the cohort in stage I MCC vs. 47.4% of patients who refused surgery), more often received care at a community cancer facility (7.4% of cohort vs. 23.7% among those patients who refused), and more often had prior chemotherapy (16.7% in the cohort vs. 23.7% who refused surgery) (p<0.001). OS rates were lower in patients who refused surgery, with one-year and five-year survival rates of 97% and 50%, respectively, compared to 98% and 54% for those who underwent surgery.

Conclusion: Surgery refusal in patients with MCC was related to poorer OS outcomes and was more common among older individuals, those treated at community cancer centers, and those with late-stage cancer. Interventions that address patient concerns and obstacles to surgery are crucial for increasing surgery acceptance and survival in these populations.

Keywords:
  • Merkel cell carcinoma
  • surgery refusal
  • overall survival

Introduction

Merkel cell carcinoma (MCC) is a rare neuroendocrine malignancy that typically presents as a growth on the skin. MCC mostly occurs among the older population (1, 2). The cancer can arise anywhere on the body; however, it mostly occurs in areas of the skin that receive frequent sun exposure (3-5). In 2013, the annual MCC incidence rate was just 0.7 per 100,000 individuals in the USA (6). Incidence has risen each year, likely due to the aging of the population, among other factors (5-7). Recent evidence suggests that in addition to ultraviolet (UV) exposure, Merkel cell polyomavirus has a strong causative role in the development of this malignancy (8, 9). MCC is an aggressive cancer with a disease-associated mortality estimated to be between 33% and 46% (9, 10), a much higher rate than patients with melanoma (11, 12). Multiple studies show that MCC presents a higher risk for men, with increased incidence and mortality rates (3, 4, 7).

Localized cases of MCC are primarily treated with surgery, as complete excision significantly improves overall survival (OS) (13). Moreover, surgery may be used for an initial accurate diagnosis and staging of the cancer (14). This evaluation of the stage of the disease is vital as MCC-specific survival rates are strongly stage-dependent (95% at 5 years for patients with pathologic stage I vs. 41% for pathologic stage IV) (2). Research suggests reduced local excision and the presence of residual tumor cells pose a risk of relapses when adjuvant radiation therapy is not performed (15, 16). Alternative techniques intended to preserve surrounding healthy tissue include Mohs surgery, modified Mohs surgery, and excision with complete circumferential peripheral and deep margin assessment (17, 18). Despite the evidence in favor of surgical intervention, some patients with MCC opt to refuse this treatment modality. Prognosis for MCC can vary widely, especially for patients who decline surgical treatment. Key factors such as tumor stage, demographic characteristics, and underlying health conditions significantly influence survival outcomes.

This study aimed to evaluate how refusal of surgery would impact OS in patients with MCC and to identify the demographic and clinical factors associated with such refusals. A greater understanding of these disparities could guide the development of strategies that address patient concerns and reduce the barriers that some groups face to care. A more effective promotion of surgical treatment utilization would ultimately improve patient outcomes. By tackling the causes of surgery refusal, healthcare providers can create targeted interventions to further adherence to surgical recommendations, thus improving survival rates for patients with MCC.

Patients and Methods

Design. The National Cancer Database (NCDB) provided data for this retrospective cohort analysis between 2004 and 2019. The American Cancer Society and the Commission on Cancer of the American College of Surgeons developed the NCDB, a clinical surveillance registry. It comprises data from over 1,500 permitted facilities and covers around 70% of new cancer cases in the USA (19). Since the NCDB data is de-identified, Institutional Review Board authorization was not needed for this study.

Study population. To identify patients with an MCC diagnosis, the NCDB was queried. Income, sex, ethnicity, race, treatment facility type, patient distance to the facility, age at diagnosis, insurance coverage by primary insurance carrier at diagnosis, and urban-rural categorization were among the sociodemographic factors. Patient distance to the treatment facility was measured as the mileage between the patient’s zip code and the facility. Income was calculated using the American Community Survey’s median household income for each patient’s zip code, adjusted for inflation. The type of treatment center was defined via the Commission on Cancer’s classification of reporting facilities based on caseload, services rendered, and program structure. The United States Department of Agriculture Economic Research Service’s rural-urban continuum codes were used to classify each patient as either rural, urban, or metro, depending on their county (20). Clinical characteristics included treatment type, stage, and grade. Staging followed the American Joint Committee on Cancer 6th and 7th edition guidelines.

Statistical analysis. The sociodemographic and clinical characteristics of the patients were compiled via descriptive statistics. Using Pearson Chi-square tests, expressed as frequencies and relative frequencies, associations between categorical variables and surgical refusal were examined. For continuous variables, represented by medians, means, and standard deviations, the Wilcoxon Rank Sum test was employed. OS was defined as the time between a cancer diagnosis and death. As indicated in Table I, factors related to OS were examined using both univariate and multivariable Cox proportional hazards models. Hazard ratios (HR), 95% confidence intervals (CI), and p-values are reported. The Kaplan–Meier (KM) method was used to analyze OS, and the log-rank test was used to compare survival curves. The KM curves included the numbers at risk. SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) was used for statistical analysis.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table I.

Cox proportional hazards model for overall survival.

Results

Patient characteristics. The study included 11,012 patients with MCC identified in the NCDB from 2004 to 2019. The demographics of these patients are shown in Table II. The mean age was 74.3 years, and 62.5% of patients were male. 97.5% of patients were White, 1.2% were Black, 0.8% were Asian or Pacific Islander, 0.2% were Native American, and 0.3% were of a different ethnicity not categorized. Additionally, 2.4% of the cohort was Hispanic. 54% of patients had stage I MCC, 22.5% had stage II, and 23.5% had stage III. Of the 9,901 patients recommended for surgery, 99.6% underwent surgery, while 0.4% refused (Table II).

View this table:
  • View inline
  • View popup
Table II.

Baseline patient characteristics stratified by surgery status and reason for non-performance.

Factors associated with surgery refusal. Patients who refused surgery had a mean age of 82.6 years, higher than the overall mean age of 74.3 years (p<0.001). While 54% of the cohort had stage I MCC, just 47.4% of patients who refused surgery had stage I of the disease (p<0.001). The facility in which a patient received treatment proved significant, with 7.4% of patients receiving treatment at a community cancer facility compared to 23.7% among those patients who refused (p<0.001). 16.7% of patients in the cohort received prior chemotherapy compared to 23.7% of those who refused surgery (p<0.001) (Table II).

Overall survival. Patients who refused surgery had shorter median survival times and lower one-year and five-year OS rates compared to patients who underwent surgery, as shown in Table III. The median survival time was 64.4 months for surgically treated patients versus 42.3 months for those who refused surgery (Table III). The log-rank test revealed statistically significant differences in OS between these groups (p<0.05) (Figure 1). Patients who underwent surgery had one-year and five-year OS rates of 98% and 54%, respectively, while those who refused surgery had rates of 97% and 50% (Table III).

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table III.

Overall survival stratified by surgery status and reason for non-performance.

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Kaplan–Meier curves for overall survival stratified by surgery status and reason for non-performance.

Discussion

This study investigated variables linked to surgery refusal and evaluated the effect of refusal on OS in patients with MCC. Compared to patients who received surgery, those who declined it had shorter median survival durations and poorer one- and five-year OS rates. Surgery refusal was associated with older age and the facility in which a patient received treatment.

The average age of patients who declined surgery was 82.6 years, 8.3 years older than the average age of 74.3 years for all patients with MCC. These findings are consistent with previous studies showing that older people have greater rates of surgery refusal (21). According to prior studies, older persons’ decisions to decline cancer treatment are significantly influenced by their worries about side effects (21, 22). Higher rates of rejection among older people are also influenced by a diminished desire to extend life and worries about safety, effects on quality of life, and treatment effectiveness (22, 23). Resolving these issues is essential to increasing the use of surgical care and raising survival rates in this population.

While 54% of the cohort had stage I MCC, just 47.4% of patients who refused surgery had stage I of the disease. This finding of patients in the later stages of cancer being more likely to refuse surgery is consistent with previous research (24, 25). This could be due to a perception of decreased benefit, fear of complications, or preference for non-surgical treatment among patients with a more advanced stage. It is possible that those with more advanced disease were more hesitant about a treatment that was more aggressive in nature. Additionally, patients with stage I MCC may have seen surgery as a more definitive treatment, while those with later stages might have been more skeptical of its upside.

The facility in which a patient received treatment proved significant, with 7.4% of patients receiving treatment at a community cancer facility compared to 23.7% among those patients who refused. This finding is consistent with previous research showing patients are more likely to refuse surgery if they are not seen at an academic or research-oriented center (26). Numerous prior studies have indicated patients in rural areas where the primary treatment facility is more likely to be a community care center refuse surgical recommendations due to cost (27, 28). Additionally, community cancer centers commonly have fewer specialized surgeons, which could lead to patients being less optimistic about the outcome of surgery (29, 30). There are also resource limitations at a community cancer center that academic or high-volume cancer centers don’t share, potentially leaving patients less comfortable with the prospect of surgical treatment at a community center (31, 32). Additionally, patients at a community cancer center may have lower health literacy, which could influence their willingness or ability to undergo surgery (33).

16.7% of patients in the cohort received prior chemotherapy compared to 23.7% of those who refused surgery. Previous studies have indicated patient concern with chemotherapy side effects and the negative effects it can have on patient mental and physical health (34-36). Patients who have undergone chemotherapy treatment may be less willing to agree to further treatments, such as surgery, after a negative experience with chemotherapy. Additionally, if prior chemotherapy was given, a patient may refuse surgery because the cancer is already being treated systemically, and they view it as offering a limited benefit.

It is essential to recognize that while our study revealed statistically significant differences in several parameters, these variations might not always have significant clinical ramifications. The dearth of MCC patient data due to the rarity of the disease raises the possibility of misleading trends, which may compromise the validity of the study. Deeper investigation of these areas is limited by the NCDB’s lack of data on recurrence, cause of death, and particular reasons for surgery refusal. NCDB data does not account for factors like cultural and religious concepts, which may have an impact on surgical refusal. Although patients who refused suggested surgery were studied separately from those who were unable to have surgery because of comorbidities or frailty, patient comorbidities were not systematically evaluated. Additionally, the study’s retrospective design has drawbacks, as the data might not accurately reflect current practices and disparities in the field. The applicability of our findings to current health care practices could shift in time due to modifications in healthcare procedures and improvements in therapeutic approaches.

Conclusion

According to this study, the OS rates of patients with MCC who declined suggested surgery were lower compared to those who underwent surgical intervention. Patients treated in community cancer centers, those who had previously received chemotherapy, those who were older, and those in later stages of the disease were all more likely to refuse surgery. These results underline the need for initiatives to guarantee equitable access to surgical care by highlighting notable differences in surgery refusal. Improving survival rates and attaining greater equity in MCC management require addressing these discrepancies.

Footnotes

  • Authors’ Contributions

    KP was responsible for writing the original draft. KP and EMG were responsible for conceptualization, methodology, investigation, and visualization. EMG was responsible for validation, formal analysis, resources, data curation, supervision, and funding acquisition. KP, BPS, SRR, SHR, RS, RP, KBS, GK, PBJ, FM, EPE, JCB, SB, SS, HKM, AA, and EMG were responsible for reviewing and editing.

  • Conflicts of Interest

    The Authors declare no conflicts of interest in relation to this study.

  • Funding

    This work was supported by Roswell Park Cancer Institute and National Cancer Institute (NCI) grant P30CA016056.

  • Received March 27, 2025.
  • Revision received April 19, 2025.
  • Accepted April 22, 2025.
  • Copyright © 2025 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Mistry K,
    2. Levell NJ,
    3. Hollestein L,
    4. Wakkee M,
    5. Nijsten T,
    6. Knott CS,
    7. Steven NM,
    8. Craig PJ,
    9. Venables ZC
    : Trends in incidence, treatment and survival of Merkel cell carcinoma in England 2004–2018: a cohort study. Br J Dermatol 188(2): 228-236, 2023. DOI: 10.1093/bjd/ljac044
    OpenUrlCrossRefPubMed
  2. ↵
    1. McEvoy AM,
    2. Lachance K,
    3. Hippe DS,
    4. Cahill K,
    5. Moshiri Y,
    6. Lewis CW,
    7. Singh N,
    8. Park SY,
    9. Thuesmunn Z,
    10. Cook MM,
    11. Alexander NA,
    12. Zawacki L,
    13. Thomas H,
    14. Paulson KG,
    15. Nghiem P
    : Recurrence and mortality risk of Merkel cell carcinoma by cancer stage and time from diagnosis. JAMA Dermatol 158(4): 382-389, 2022. DOI: 10.1001/jamadermatol.2021.6096
    OpenUrlCrossRefPubMed
  3. ↵
    1. Albores-Saavedra J,
    2. Batich K,
    3. Chable-Montero F,
    4. Sagy N,
    5. Schwartz AM,
    6. Henson DE
    : Merkel cell carcinoma demographics, morphology, and survival based on 3870 cases: a population based study. J Cutan Pathol 37(1): 20-27, 2010. DOI: 10.1111/j.1600-0560.2009.01370.x
    OpenUrlCrossRefPubMed
  4. ↵
    1. Uitentuis SE,
    2. Louwman MW,
    3. van Akkooi AC,
    4. Bekkenk MW
    : Treatment and survival of Merkel cell carcinoma since 1993: A population-based cohort study in The Netherlands. J Am Acad Dermatol 81(4): 977-983, 2019. DOI: 10.1016/j.jaad.2019.01.042
    OpenUrlCrossRefPubMed
  5. ↵
    1. Girschik J,
    2. Thorn K,
    3. Beer TW,
    4. Heenan PJ,
    5. Fritschi L
    : Merkel cell carcinoma in Western Australia: a population-based study of incidence and survival. Br J Dermatol 165(5): 1051-1057, 2011. DOI: 10.1111/j.1365-2133.2011.10493.x
    OpenUrlCrossRefPubMed
  6. ↵
    1. Paulson KG,
    2. Park SY,
    3. Vandeven NA,
    4. Lachance K,
    5. Thomas H,
    6. Chapuis AG,
    7. Harms KL,
    8. Thompson JA,
    9. Bhatia S,
    10. Stang A,
    11. Nghiem P
    : Merkel cell carcinoma: Current US incidence and projected increases based on changing demographics. J Am Acad Dermatol 78(3): 457-463.e2, 2018. DOI: 10.1016/j.jaad.2017.10.028
    OpenUrlCrossRefPubMed
  7. ↵
    1. Lee Y,
    2. Chao P,
    3. Coomarasamy C,
    4. Mathy JA
    : Epidemiology and survival of Merkel cell carcinoma in New Zealand: A population-based study between 2000 and 2015 with international comparison. Australas J Dermatol 60(4): e284-e291, 2019. DOI: 10.1111/ajd.13023
    OpenUrlCrossRefPubMed
  8. ↵
    1. Feng H,
    2. Shuda M,
    3. Chang Y,
    4. Moore PS
    : Clonal integration of a polyomavirus in human Merkel cell carcinoma. Science 319(5866): 1096-1100, 2008. DOI: 10.1126/science.1152586
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Chang Y,
    2. Moore PS
    : Merkel cell carcinoma: a virus-induced human cancer. Annu Rev Pathol 7: 123-144, 2012. DOI: 10.1146/annurev-pathol-011110-130227
    OpenUrlCrossRefPubMed
  10. ↵
    1. Becker JC
    : Merkel cell carcinoma. Ann Oncol 21: vii81-vii85, 2010. DOI: 10.1093/annonc/mdq366
    OpenUrlCrossRefPubMed
  11. ↵
    1. Lemos BD,
    2. Storer BE,
    3. Iyer JG,
    4. Phillips JL,
    5. Bichakjian CK,
    6. Fang LC,
    7. Johnson TM,
    8. Liegeois-Kwon NJ,
    9. Otley CC,
    10. Paulson KG,
    11. Ross MI,
    12. Yu SS,
    13. Zeitouni NC,
    14. Byrd DR,
    15. Sondak VK,
    16. Gershenwald JE,
    17. Sober AJ,
    18. Nghiem P
    : 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 63(5): 751-761, 2010. DOI: 10.1016/j.jaad.2010.02.056
    OpenUrlCrossRefPubMed
  12. ↵
    1. Miller RW,
    2. Rabkin CS
    : Merkel cell carcinoma and melanoma: etiological similarities and differences. Cancer Epidemiol Biomarkers Prev 8(2): 153-158, 1999.
    OpenUrlAbstract/FREE Full Text
  13. ↵
    1. Tai PT,
    2. Yu E,
    3. Tonita J,
    4. Gilchrist J
    : Merkel cell carcinoma of the skin. J Cutan Med Surg 4(4): 186-195, 2000. DOI: 10.1177/120347540000400403
    OpenUrlCrossRefPubMed
  14. ↵
    1. Schmults CD,
    2. Blitzblau R,
    3. Aasi SZ,
    4. Alam M,
    5. Amini A,
    6. Bibee K,
    7. Bolotin D,
    8. Bordeaux J,
    9. Chen PL,
    10. Contreras CM,
    11. DiMaio D,
    12. Donigan JM,
    13. Farma JM,
    14. Ghosh K,
    15. Harms K,
    16. Ho AL,
    17. Lukens JN,
    18. Manber S,
    19. Mark L,
    20. Medina T,
    21. Nehal KS,
    22. Nghiem P,
    23. Olino K,
    24. Park S,
    25. Patel T,
    26. Puzanov I,
    27. Rich J,
    28. Sekulic A,
    29. Shaha AR,
    30. Srivastava D,
    31. Thomas V,
    32. Tomblinson C,
    33. Venkat P,
    34. Xu YG,
    35. Yu S,
    36. Yusuf M,
    37. McCullough B,
    38. Espinosa S
    : NCCN Guidelines® Insights: Merkel Cell Carcinoma, Version 1.2024. Journal of the National Comprehensive Cancer Network 22(1D): 1-11, 2024. DOI: 10.6004/jnccn.2024.0002
    OpenUrlCrossRefPubMed
  15. ↵
    1. Andruska N,
    2. Mahapatra L,
    3. Brenneman RJ,
    4. Rich JT,
    5. Baumann BC,
    6. Compton L,
    7. Thorstad WL,
    8. Daly MD
    : Reduced wide local excision margins are associated with increased risk of relapse and death from Merkel cell carcinoma. Ann Surg Oncol 28(6): 3312-3319, 2021. DOI: 10.1245/s10434-020-09145-7
    OpenUrlCrossRefPubMed
  16. ↵
    1. Mattavelli I,
    2. Patuzzo R,
    3. Torri V,
    4. Gallino G,
    5. Maurichi A,
    6. Lamera M,
    7. Valeri B,
    8. Bolzonaro E,
    9. Barbieri C,
    10. Tolomio E,
    11. Moglia D,
    12. Nespoli AM,
    13. Galeone C,
    14. Saw R,
    15. Santinami M
    : Prognostic factors in Merkel cell carcinoma patients undergoing sentinel node biopsy. Eur J Surg Oncol 43(8): 1536-1541, 2017. DOI: 10.1016/j.ejso.2017.05.013
    OpenUrlCrossRefPubMed
  17. ↵
    1. Kline L,
    2. Coldiron B
    : Mohs micrographic surgery for the treatment of Merkel cell carcinoma. Dermatol Surg 42(8): 945-951, 2016. DOI: 10.1097/DSS.0000000000000801
    OpenUrlCrossRefPubMed
  18. ↵
    1. Singh B,
    2. Qureshi MM,
    3. Truong MT,
    4. Sahni D
    : Demographics and outcomes of stage I and II Merkel cell carcinoma treated with Mohs micrographic surgery compared with wide local excision in the National Cancer Database. J Am Acad Dermatol 79(1): 126-134.e3, 2018. DOI: 10.1016/j.jaad.2018.01.041
    OpenUrlCrossRefPubMed
  19. ↵
    1. Bertakis KD,
    2. Azari R,
    3. Helms LJ,
    4. Callahan EJ,
    5. Robbins JA
    : Gender differences in the utilization of health care services. J Fam Pract 49(2): 147-152, 2000.
    OpenUrlPubMed
  20. ↵
    1. American College of Surgeons
    : National Cancer Database (NCDB) Participant User File Data Dictionary (2019). Published 2019. Available at: https://www.facs.org/media/aq3aummh/puf_data_dictionary_2019.pdf [Last accessed on April 22, 2025]
  21. ↵
    1. Dias LM,
    2. Bezerra MR,
    3. Barra WF,
    4. Rego F
    : Refusal of medical treatment by older adults with cancer: a systematic review. Ann Palliat Med 10(4): 4868-4877, 2021. DOI: 10.21037/apm-20-2439
    OpenUrlCrossRefPubMed
  22. ↵
    1. Angarita FA,
    2. Elmi M,
    3. Zhang Y,
    4. Look Hong NJ
    : Patient-reported factors influencing the treatment decision-making process of older women with non-metastatic breast cancer: a systematic review of qualitative evidence. Breast Cancer Res Treat 171(3): 545-564, 2018. DOI: 10.1007/s10549-018-4865-0
    OpenUrlCrossRefPubMed
  23. ↵
    1. Rocque GB,
    2. Rasool A,
    3. Williams BR,
    4. Wallace AS,
    5. Niranjan SJ,
    6. Halilova KI,
    7. Turkman YE,
    8. Ingram SA,
    9. Williams CP,
    10. Forero-Torres A,
    11. Smith T,
    12. Bhatia S,
    13. Knight SJ
    : What is important when making treatment decisions in metastatic breast cancer? A qualitative analysis of decision-making in patients and oncologists. Oncologist 24(10): 1313-1321, 2019. DOI: 10.1634/theoncologist.2018-0711
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Rapp J,
    2. Tuminello S,
    3. Alpert N,
    4. Flores RM,
    5. Taioli E
    : Disparities in surgery for early-stage cancer: the impact of refusal. Cancer Causes Control 30(12): 1389-1397, 2019. DOI: 10.1007/s10552-019-01240-9
    OpenUrlCrossRefPubMed
  25. ↵
    1. Relation T,
    2. Ndumele A,
    3. Bhattacharyya O,
    4. Fisher JL,
    5. Li Y,
    6. Obeng-Gyasi S,
    7. Eskander MF,
    8. Tsung A,
    9. Oppong BA
    : Surgery refusal among Black and Hispanic women with non-metastatic breast cancer. Ann Surg Oncol 29(11): 6634-6643, 2022. DOI: 10.1245/s10434-022-11832-6
    OpenUrlCrossRefPubMed
  26. ↵
    1. Tohme S,
    2. Kaltenmeier C,
    3. Bou-samra P,
    4. Varley PR,
    5. Tsung A
    : Race and health disparities in patient refusal of surgery for early-stage pancreatic cancer: an NCDB cohort study. Ann Surg Oncol 25(12): 3427-3435, 2018. DOI: 10.1245/s10434-018-6680-6
    OpenUrlCrossRefPubMed
  27. ↵
    1. Palmer NR,
    2. Geiger AM,
    3. Lu L,
    4. Case LD,
    5. Weaver KE
    : Impact of rural residence on forgoing healthcare after cancer because of cost. Cancer Epidemiol Biomarkers Prev 22(10): 1668-1676, 2013. DOI: 10.1158/1055-9965.EPI-13-0421
    OpenUrlAbstract/FREE Full Text
  28. ↵
    1. Gonzalo MB,
    2. House L,
    3. Santiago K,
    4. Buzaglo JS,
    5. Zaleta AK,
    6. Gupta NK
    : Access to care in cancer: Barriers and challenges. J Clin Oncol 35(8_suppl): 33-33, 2017. DOI: 10.1200/JCO.2017.35.8_suppl.33
    OpenUrlCrossRef
  29. ↵
    1. US Government Accountability Office
    : Physician Workforce: Locations and Types of Graduate Training Were Largely Unchanged, and Federal Efforts May Not Be Sufficient to Meet Needs. Washington DC, USA. GAO, 2017. Available at: https://www.gao.gov/products/gao-17-411 [Last accessed on March 7, 2025]
  30. ↵
    1. Kirkwood MK,
    2. Bruinooge SS,
    3. Goldstein MA,
    4. Bajorin DF,
    5. Kosty MP
    : Enhancing the American Society of Clinical Oncology Workforce Information System with geographic distribution of oncologists and comparison of data sources for the number of practicing oncologists. J Oncol Pract 10(1): 32-38, 2014. DOI: 10.1200/JOP.2013.001311
    OpenUrlAbstract/FREE Full Text
  31. ↵
    1. National Association of Social Workers
    : Assuring the Sufficiency of a Frontline Workforce: A National Study of Licensed Social Workers. Washington DC, USA. 2006. Available at: https://www.socialworkers.org/LinkClick.aspx?fileticket=OilZ7p_EEnE%3D&portalid=0 [Last accessed on March 7, 2025]
  32. ↵
    1. Reschovsky JD,
    2. Staiti AB
    : Access and quality: does rural America lag behind? Health Aff (Millwood) 24(4): 1128-1139, 2005. DOI: 10.1377/hlthaff.24.4.1128
    OpenUrlAbstract/FREE Full Text
  33. ↵
    1. Martinez-Donate AP,
    2. Halverson J,
    3. Simon NJ,
    4. Strickland JS,
    5. Trentham-Dietz A,
    6. Smith PD,
    7. Linskens R,
    8. Wang X
    : Identifying health literacy and health system navigation needs among rural cancer patients: findings from the Rural Oncology Literacy Enhancement Study (ROLES). J Cancer Educ 28(3): 573-581, 2013. DOI: 10.1007/s13187-013-0505-x
    OpenUrlCrossRefPubMed
  34. ↵
    1. Li P,
    2. Li F,
    3. Fang Y,
    4. Wan D,
    5. Pan Z,
    6. Chen G,
    7. Ma G
    : Efficacy, compliance and reasons for refusal of postoperative chemotherapy for elderly patients with colorectal cancer: a retrospective chart review and telephone patient questionnaire. PLoS One 8(2): e55494, 2013. DOI: 10.1371/journal.pone.0055494
    OpenUrlCrossRefPubMed
    1. Grassi L,
    2. Berardi MA,
    3. Ruffilli F,
    4. Meggiolaro E,
    5. Andritsch E,
    6. Sirgo A,
    7. Caruso R,
    8. Juan Linares E,
    9. Bellé M,
    10. Massarenti S,
    11. Nanni MG, IOR-IRST Psycho-Oncology and UniFE Psychiatry Co-Authors
    : Role of psychosocial variables on chemotherapy-induced nausea and vomiting and health-related quality of life among cancer patients: a European study. Psychother Psychosom 84(6): 339-347, 2015. DOI: 10.1159/000431256
    OpenUrlCrossRefPubMed
  35. ↵
    1. Kamen C,
    2. Tejani MA,
    3. Chandwani K,
    4. Janelsins M,
    5. Peoples AR,
    6. Roscoe JA,
    7. Morrow GR
    : Anticipatory nausea and vomiting due to chemotherapy. Eur J Pharmacol 722: 172-179, 2014. DOI: 10.1016/j.ejphar.2013.09.071
    OpenUrlCrossRefPubMed
PreviousNext
Back to top

In this issue

Anticancer Research: 45 (6)
Anticancer Research
Vol. 45, Issue 6
June 2025
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Back Matter (PDF)
  • Ed Board (PDF)
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Anticancer Research.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Impact of Surgery Refusal on Overall Survival in Merkel Cell Carcinoma
(Your Name) has sent you a message from Anticancer Research
(Your Name) thought you would like to see the Anticancer Research web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
10 + 2 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Impact of Surgery Refusal on Overall Survival in Merkel Cell Carcinoma
KYLE POPP, REED POPP, JADE BOWERS, SYEDA HOORULAIN AHMED, RAMIN SHEKOUHI, SHIVAM BANSAL, SEEMA SHARAN, HARSHEEN K. MANAISE, BANSI P. SAVALIY, SWATHI R. RAIKOT, PAOLA BERRIOS JIMENEZ, FATIMA MUBARAK, ESINAM P. EKPEH, KULKAEW B. SUKNIAM, GABRIELLE KOWKABANY, ANGEL AGUAYO, EMMANUEL M. GABRIEL
Anticancer Research Jun 2025, 45 (6) 2443-2451; DOI: 10.21873/anticanres.17615

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Reprints and Permissions
Share
Impact of Surgery Refusal on Overall Survival in Merkel Cell Carcinoma
KYLE POPP, REED POPP, JADE BOWERS, SYEDA HOORULAIN AHMED, RAMIN SHEKOUHI, SHIVAM BANSAL, SEEMA SHARAN, HARSHEEN K. MANAISE, BANSI P. SAVALIY, SWATHI R. RAIKOT, PAOLA BERRIOS JIMENEZ, FATIMA MUBARAK, ESINAM P. EKPEH, KULKAEW B. SUKNIAM, GABRIELLE KOWKABANY, ANGEL AGUAYO, EMMANUEL M. GABRIEL
Anticancer Research Jun 2025, 45 (6) 2443-2451; DOI: 10.21873/anticanres.17615
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Patients and Methods
    • Results
    • Discussion
    • Conclusion
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • No citing articles found.
  • Google Scholar

More in this TOC Section

  • Tumor Budding Grade and T Stage as Recurrence Predictors of High-risk Stage II Colorectal Cancer
  • Pathologic Complete Response (pCR) in Patient With Myxofibrosarcoma Who Underwent Neoadjuvant Radiation Concurrent to Complementary and Alternative Medicine
  • Machine Learning Model to Guide Empirical Antimicrobial Therapy in Febrile Neutropenic Patients With Hematologic Malignancies
Show more Clinical Studies

Similar Articles

Keywords

  • Merkel cell carcinoma
  • surgery refusal
  • overall survival
Anticancer Research

© 2025 Anticancer Research

Powered by HighWire