Next Article in Journal
Breast Cancer Stem Cells and Tumor Heterogeneity: Characteristics and Therapeutic Strategies
Previous Article in Journal
Overcoming Chemoresistance in Cancer: The Promise of Crizotinib
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Lack of Clinically Significant Relationships of Age or Body Mass Index with Merkel Cell Carcinoma Immunotherapy Outcomes

1
Department of Dermatology, University of Washington, Seattle, WA 98109, USA
2
Fred Hutchinson Cancer Center, Clinical Research Division, Seattle, WA 98109, USA
3
Division of Hematology/Oncology, Department of Medicine, University of Washington, Seattle, WA 98109, USA
4
College of Osteopathic Medicine, Pacific Northwest University of Health Sciences, Yakima, WA 98901, USA
*
Author to whom correspondence should be addressed.
Cancers 2024, 16(13), 2480; https://doi.org/10.3390/cancers16132480
Submission received: 15 June 2024 / Revised: 2 July 2024 / Accepted: 3 July 2024 / Published: 7 July 2024
(This article belongs to the Section Cancer Immunology and Immunotherapy)

Abstract

:

Simple Summary

Merkel cell carcinoma is a rare, aggressive skin cancer prone to spreading. While anti-PD-1/PD-L1 immunotherapy has improved outcomes for advanced MCC, about half of such patients do not see long-lasting benefits. This study examined how age and body mass index (BMI) affect the response to immunotherapy in 183 advanced MCC patients from a single-center-based, longitudinal database. The analysis showed that age impacts treatment response, with patients significantly older than 70 years responding less effectively. However, age did not influence other outcomes, including progression-free survival, MCC-specific survival, and overall survival. Similarly, BMI did not significantly affect any immunotherapy outcomes. These results suggest that age and BMI should not be used to determine immunotherapy eligibility in MCC, highlighting the need for unbiased patient selection for this treatment.

Abstract

Merkel cell carcinoma (MCC) is a rare and aggressive skin cancer with a high risk of metastasis. The development of anti-PD-1/PD-L1 immunotherapy has improved outcomes for advanced MCC, yet about 50% of such patients do not achieve durable responses. This study analyzed the effects of age and body mass index (BMI) on immunotherapy response in 183 advanced MCC patients from a single-center longitudinal database. Using Fine–Gray or Cox regression models, treatment response, progression-free survival (PFS), MCC-specific survival, and overall survival (OS) were evaluated. Age showed a significant non-linear relationship with treatment response (p = 0.04), with patients much older or younger than 70 years less likely to respond. However, age was not significantly associated with PFS (p = 0.21), MCC-specific survival (p = 0.72), or OS (p = 0.36). Similarly, BMI was not significantly correlated with treatment response (p = 0.41), PFS (p = 0.52), MCC-specific survival (p = 0.78), or OS (p = 0.71). Unlike previous studies suggesting that obesity and advanced age improve outcomes in other cancers, these associations were not observed in MCC. These findings suggest that age and BMI should not influence eligibility for immunotherapy in MCC patients, emphasizing the importance of unbiased patient selection for this treatment.

1. Introduction

Merkel cell carcinoma (MCC) is an aggressive skin cancer with a rising incidence, predominantly affecting older adults [1,2]. Approximately 40% of patients are diagnosed at an advanced stage, and 40% of MCC patients experience recurrences following standard treatment, often necessitating systemic interventions [3].
Immunotherapy has emerged as the preferred first-line treatment for advanced-stage MCC [4]. Compared to chemotherapy, the previous standard of care, anti-PD-1/PD-L1 immunotherapy offers a comparable response rate of ~50%, vastly improved durability of response, and a favorable toxicity profile [5,6,7,8,9,10,11]. Despite the success of immunotherapy in MCC, more than 50% of patients do not persistently benefit from PD-1/PD-L1 immunotherapies [6,12].
As immunotherapy has become the dominant approach for treating advanced disease across various cancers, multiple studies have sought to identify factors influencing immunotherapy efficacy [13]. Research in other cancers, including melanoma, lung cancer, and renal cell carcinoma has suggested an association between age or body mass index (BMI) and immunotherapy response [14,15,16,17,18]. In this study, we investigated how age and BMI may correlate with immunotherapy response in MCC, utilizing a large longitudinal database of MCC patients.

2. Methods

2.1. Patient Selection

An IRB-approved, Seattle-based repository of MCC patients who enrolled between 2012 and 2021 was analyzed, retrospectively. This longitudinal database contains relevant clinical features and long-term follow-up information, and it is updated at least annually with information extracted from documented patient communication and medical records. Informed consent was obtained from all subjects involved in the study.
Only patients enrolled in the repository ≤180 days from the start of immunotherapy and prior to disease progression were included in this study to avoid ascertainment bias toward patients with worse outcomes. Patients who had histologically confirmed unresectable stage III or IV MCC (American Joint Committee on Cancer 8th Edition [19]) received first-line treatment with PD-1/L-1 immunotherapy, and had follow-up information available for response, progression, and survival outcomes. Clinical data collected at time of immunotherapy initiation included age, BMI, sex, disease stage, immunosuppression status, and ECOG performance status (Eastern Cooperative Oncology Group). BMI calculations at the start date of immunotherapy followed the National Institute of Health guidelines, computed as the ratio of weight in kilograms divided by the square of height in meters. Patient age was determined as years between date of birth and initiation of immunotherapy.

2.2. Outcome Measurements

Tumor response was classified as either progressive disease (PD), stable disease (SD), partial response (PR), or complete response (CR) in accordance with the Response Evaluation Criteria In Solid Tumors (RECIST version 1.1).
Time to objective response was determined as the time from immunotherapy initiation to the first time a CR or PR was documented, with death or progressive disease considered as competing risks. Progression-free survival (PFS) was defined as the time from immunotherapy initiation to either progressive disease, recurrence, or death. MCC-specific survival was defined as the time from immunotherapy initiation to patient death by MCC, with death from other causes considered as a competing risk. Overall survival (OS) was defined as the time from immunotherapy initiation to patient death due to all causes.

2.3. Statistical Considerations

All analyses were conducted using R (version 4.3.2, R Foundation for Statistical Computing). All statistical tests were two-sided and statistical significance was defined as p < 0.05. Associations of age and BMI with each outcome after immunotherapy were assessed using Fine–Gray regression models for outcomes with competing risks (objective response and MCC-specific survival) and Cox regression models for outcomes without competing risks (PFS and OS). Multivariable models included age, BMI, ECOG performance status (0 vs. 1+), gender, stage of disease (III vs. IV), and immunosuppression. In the primary analysis, age and BMI were treated as continuous variables, as opposed to being divided into discrete categories, to maximize statistical power and avoid threshold-dependent results. Potential non-linear relationships of age or BMI with outcomes were examined using restricted cubic splines with three knots. Knots were placed by default at the 10th, 50th (median), and 90th percentiles of the age or BMI distribution. The regression coefficient corresponding to non-linear portion of the restricted cubic spline was tested against zero using a Wald test. Relationships between age or BMI and each outcome were modeled as linear unless the test for a non-linear component was statistically significant. As a sensitivity analysis and to facilitate comparisons with other studies which categorized these variables, the analyses of age and BMI versus outcomes were repeated but with both factors categorized in different ways. Age was either categorized into four groups (<60, 60–69, 70–79, and ≥80 years) [20] or two groups (≤75 and >75 years) [21]. BMI was dichotomized two ways, either as ≥25 kg/m2 vs. <25 kg/m2 [17] or ≥30 kg/m2 vs. <30 kg/m2 [21].

3. Results

3.1. Clinical Characteristics of Cohort

A total of 183 patients were identified as eligible, with 140 male patients (76.5%) and 43 female patients (23.5%), with a median age of 70 (range: 19 to 91). Among the 169 patients (92%) with available BMI data, the median BMI was 30.0 kg/m2 (range: 19.4 to 58.7 kg/m2). A total of 33 patients had a BMI between 18.5 and 24.9 kg/m2 (19.5%), 61 patients with a BMI between 25 and 29.9 kg/m2 (36.1%), and 75 patients with BMI ≥ 30 kg/m2 (44.4%). A total of 167 patients had ECOG status 0 or 1 (93.3%). A total of 91 patients (51.1%) were seropositive for MCPyV oncoprotein antibody, 87 patients (48.9%) were seronegative, and 5 patients had no data available. There were 67 patients with unresectable stage III disease (36.6%) and 116 patients with stage IV disease (63.4%). Thirty-six patients (19.7%) had chronic immunosuppression. The age distribution in immunosuppressed and immunocompetent patients were similar, with both groups having a median age of 70 years (p = 0.64). The percentage of immunosuppression was slightly higher in the <60 age group (7/26, 27%) compared to the others (29/157, 18%) but this was not statistically significant (p = 0.30). Within this cohort, 106 patients (58.0%) received pembrolizumab, 54 patients received avelumab (29.5%), 20 patients (10.9%) received nivolumab, and 3 patients (1.6%) received nivolumab + ipilimumab. Detailed clinical features are summarized in Table 1.

3.2. Outcomes

The median follow-up time for this cohort was 27 months (range 0.7–81.6). Overall, the objective response rate at 6 months was 59.16% (95% CI: 51.47, 66.04). Estimated PFS, OS, and MCC-specific survival with 95% CI at 2 years were 53.03% (45.9, 61.23), 68.39% (61.58, 75.94), and 27.32% (20.69%, 34.35), respectively. The median time to objective response was 6.5 months. The median PFS and OS times were 29.6 months and 67 months, respectively, while the median MCC-specific survival time was not reached in this cohort.

3.3. Association of Age with Outcomes

Associations between age and each outcome are summarized in Table 2 and Figure 1. Age had a statistically significant, non-linear association with objective response (p = 0.04), where patients much older or younger than the median age of 70 were less likely to respond to immunotherapy than patients around age 70. This decreased likelihood of response was more pronounced for older patients, where 80-year-old patients had a 33% reduced rate of response compared to 70-year-old patients (HR = 0.67, 95% CI: 0.46–0.99%, p = 0.04). Sixty-year-old patients had an 11% reduced rate of response compared to 70-year-old patients (HR = 0.89, 95% CI: 0.71–1.11, p = 0.30), though this decrease did not reach statistical significance.
By contrast, age was not statistically significantly associated with PFS (HR: 1.14 per 10-year increase, 95% CI: 0.93,1.41, p = 0.21), MCC-specific survival (HR:1.05 per 10-year increase, 95% CI: 0.80, 1.37, p = 0.72), or OS (HR: 1.12 per 10-year increase, 95% CI: 0.88, 1.42, p = 0.36, Table 2).
As a sensitivity analysis to facilitate comparisons with other studies, analyses with age were repeated with age categorized into four groups (<60, 60–69, 70–79, and ≥80 years) or two groups (≤75 and >75 years) and are summarized in Supplemental Table S1. When age was categorized as four groups, the 60–69 year (HR: 2.08, 95% CI: 1.10, 3.95, p = 0.025) and 70–79 year groups (HR: 1.62, 95% CI: 0.85, 3.10, p = 0.14) tended to have a high rate of objective response than the <60 year group. The <60 year group and ≥80 year groups had similar objective responses rates (HR: 1.02 [ref: <60 years], 95% CI: 0.43, 2.42, p = 0.96).

3.4. Association of BMI with Outcomes

Associations between BMI and each outcome are summarized in Table 2 and Figure 1. BMI was not statistically significantly associated with objective response (HR: 1.09 per 5 kg/m2 increase, 95% CI: 0.89, 1.33, p = 0.41), PFS (HR: 0.95 per 5 kg/m2 increase, 95% CI: 0.80, 1.12, p = 0.52), MCC-specific survival (HR: 0.97 per 5 kg/m2 increase, 95% CI: 0.79, 1.20, p = 0.78), or OS (HR: 0.96 per 5 kg/m2 increase, 95% CI (0.79,1.17), p = 0.71).
In sensitivity analyses, BMI was dichotomized as BMI ≥ 25 kg/m2 vs. BMI < 25 kg/m2 and BMI ≥ 30 kg/m2 vs. BMI < 30 kg/m2, results of which are summarized in Supplemental Table S2. In these additional analyses, BMI was not significantly associated with any of the four outcomes when dichotomized as BMI ≥ 25 kg/m2 (p = 0.46–0.75) or when dichotomized as BMI ≥ 30 kg/m2 (p = 0.38–0.82).

4. Discussion

PD-1/PD-L1 immunotherapy represents a significant advancement in cancer therapy [22]. Notably, in MCC over 50% of patients experience an objective response to immunotherapy. Numerous studies have explored clinical characteristics and biomarkers that may be predictive of immunotherapy response in MCC, although strongly predictive markers have proven elusive [23,24]. Prior studies have identified advanced age and higher BMI as being associated with a higher likelihood of immunotherapy response in several different types of solid tumors. The underlying mechanisms for these associations are not well understood. Notably, these associations have not been thoroughly examined in the context of MCC, a cancer that is particularly responsive to immunotherapy.
In our analysis, BMI did not show a significant correlation with immunotherapy outcomes in MCC. Conversely, age demonstrated a significant association with the rate of objective response; older individuals were found to be less likely to achieve an objective response, though age did not significantly affect other outcomes like PFS, OS, or disease-specific survival.

4.1. Age and PD-1/PD-L1 Immunotherapy Response and Long-Term Outcomes

Previous studies in melanoma, renal cell carcinoma, and non-small cell lung cancer have indicated improved immunotherapy outcomes associated with advancing age [16,20,25]. As reported in Kugel et al. [14], melanoma patients with age ≥62 had better responses to anti-PD-1 therapy. However, this association was relatively weak, with the odds of response only increasing by 13% per 10-year increase in age. This modest increase in response rate with age is consistent with the small increase we observed up to age 70 in our cohort of MCC patients. However, we also observed a more rapid decrease in response rate after age 70 (HR = 0.67 for age 80 vs. age 70, p = 0.04), which differs substantially from the melanoma cohort.
In a study by Lichenstein et al. [20] investigating non-small cell lung cancer among 245 patients, it was found that patients between 70 and 79 years had a significantly lower hazard for disease progression or death (hazard ratio: 0.60, p = 0.015) than younger patients, though PFS tended to be worse for patients ≥ 80 years old (HR: 1.62, p = 0.098).
In our cohort, we did not observe significantly better PFS for patients 70–79 vs. <60 (HR: 1.06, 95% CI: 0.54–2.07, p = 0.86, Supplemental Table S1), though the confidence interval includes the HR of 0.60 that Lichtenstein et al. [20] estimated. Our results for patients aged 80 and older were quite similar to Lichtenstein’s findings (HR: 1.89, p = 0.11).
Prior studies have suspected various potential mechanisms that relate to immune changes associated with age [26,27]. A recent study noted that aging is associated with increased tumor mutational burden, decreased promoter methylation and elevated expression of immune checkpoint genes, potentially leading to greater efficacy of immune checkpoint targeted therapies [28]. However, no definitive mechanism has been clearly elucidated. Further research should be conducted to investigate the various factors associated with aging that may potentially impact immunotherapy responses.

4.2. BMI and PD-1/PD-L1 Immunotherapy Response and Long-Term Outcomes

In several solid cancer types, a positive correlation has been observed between higher BMI and immunotherapy response [17,21,29,30]. In a study of renal cell carcinoma, higher BMI was associated with a small improvement in OS and PFS in two large cohorts (n = 1975 and 4657, HR: 0.81–0.86 for BMI ≥ 25 kg/m2 vs. <25 kg/m2) [17]. Another retrospective study by Wang et al. [18] involving 250 cancer patients, including those with lung cancer, ovarian cancer, or melanoma, found that obesity (BMI ≥ 30 kg/m2) was associated with improved progression-free survival (HR: 0.61, 95% CI: 0.42–0.89, p = 0.01) and overall survival (HR: 0.59, 95% CI: 0.35–0.99, p = 0.048) after adjusting for other risk factors. Similarly, a recent small (n = 32) European study by Incorvaia et al. [21] examined the impact of BMI on MCC immunotherapy outcomes and found that a BMI ≥ 30 kg/m2 was associated with significantly lower likelihood of MCC recurrence compared to a BMI < 30 kg/m2 (HR: 0.18, p = 0.04).
However, our cohort experienced a much smaller association of BMI ≥ 30 kg/m2 with MCC recurrence following IMTX (HR: 0.94, 95% CI: 0.62–1.44, p = 0.79) as compared to that of Incorvaia et al. [21]. Our confidence interval strongly excludes a hypothesis of HR = 0.18 from the Incorvaia study but only marginally excludes a hypothesis of HR = 0.61 from the Wang study. Both our study and the Incorvaia study are specific to MCC, but there are notable differences in the cohorts. The Incorvaia study included only patients treated with avelumab, while our study included patients treated with pembrolizumab, nivolumab, and avelumab. The median age in the Incorvaia study was 75, compared to 70 in our study, suggesting that age-related differences are unlikely to significantly affect the results. Our study may better reflect real-world experiences as the cohort size is six times larger and includes patients treated with both PD-1 and PD-L1 immunotherapy.
It should be acknowledged that BMI has limitations as an obesity assessment tool due to its inability to differentiate between adipose tissue and muscle [31]. Further investigation is needed to better understand the relationship between higher BMI and its effects on immune function, ideally using techniques that differentiate adipose tissue from muscle. Future research may also focus on linking obesity with changes in the gut microbiota. The composition of the gut microbiota, such as the quantity and diversity of said bacterium, has already been linked to play an important role in modulating responses to immunotherapy treatment [32].

4.3. Study Limitations

Limitations of this study include its retrospective nature and the relatively small cohort size, a consequence of the rarity of this cancer. However, to the best of our knowledge, this study represents the largest investigation into the potential correlation between BMI or age and immunotherapy response in MCC.

5. Conclusions

Our study shows no clinically significant relationship between age, BMI, and response to IMTX for MCC. With 183 patients, we may have not been able to detect small associations between age or BMI and outcomes. However, the 95% confidence intervals for the corresponding hazard ratios suggest that any associations, if present, are likely not substantial enough to impact clinical decision-making. Our findings strongly indicate that older age and increased BMI should not discourage the use of immunotherapy as a treatment option and underscore the continued viability of PD1/PD-L1 immunotherapy as a first-line treatment for advanced MCC.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers16132480/s1, Table S1: Multivariable associations of age with outcomes after grouping age in different ways; Table S2: Multivariable associations of body mass index (BMI) with outcomes after grouping age in different ways.

Author Contributions

R.A. authored the primary draft of the manuscript. E.G. and E.H. collected data from clinical records, and X.F. and D.S.H. performed statistical analyses. L.M.T., P.N. and S.Y.P. provided senior oversight and helped prepare the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

P01 CA225517 (NIH/NCI), P30 CA015704 (NIH/NCI), Kelsey Dickson Team Science Courage Research Award (Prostate Cancer Foundation), MCC Gift Fund (University of Washington).

Institutional Review Board Statement

All studies were performed in accordance with the Helsinki principles and were approved by the Institutional Review Board at the Fred Hutchinson Cancer Center (IRB #6585).

Informed Consent Statement

All patients included in this study provided informed consent for their clinical data to be analyzed for research purposes.

Data Availability Statement

The data presented in this study are available in this article and Supplementary Materials.

Conflicts of Interest

P.N. reports a consulting role at Almirall and a leadership role for the Society of Investigative Dermatology and research grant funding from Incyte; P.N. has received honoraria from Wolters Kluwer Health; P.N. reports patent filed for “Merkel cell polyomavirus T antigen-specific TCRs and uses thereof” and patent pending for high-affinity T cell receptors that target the Merkel polyomavirus. D.S.H. has received research funding from GE Healthcare. L.T. reports research grant funding (to institution) from Seagen and Merck. The remaining authors declare no conflicts of interest.

References

  1. 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]
  2. Siqueira, S.M.; Campos-do-Carmo, G.; Santos, A.L.S.D.; Martins, C.; Melo, A.C.D. Merkel cell carcinoma: Epidemiology, clinical features, diagnosis and treatment of a rare disease. An. Bras. Dermatol. 2023, 98, 277–286. [Google Scholar] [CrossRef]
  3. McEvoy, A.M.; Hippe, D.S.; Lachance, K.; Park, S.; Cahill, K.; Redman, M.; Gooley, T.; Kattan, M.W.; Nghiem, P. Merkel cell carcinoma recurrence risk estimation is improved by integrating factors beyond cancer stage: A multivariable model and web-based calculator. J. Am. Acad. Dermatol. 2024, 90, 569–576. [Google Scholar] [CrossRef]
  4. Schmults, C.D.; Blitzblau, R.; Aasi, S.Z.; Alam, M.; Amini, A.; Bibee, K.; Bolotin, D.; Bordeaux, J.; Chen, P.L.; Espinosa, S.; et al. NCCN Guidelines® Insights: Merkel Cell Carcinoma, Version 1.2024. J. Natl. Compr. Cancer Netw. 2024, 22, e240002. [Google Scholar]
  5. Cowey, C.L.; Mahnke, L.; Espirito, J.; Helwig, C.; Oksen, D.; Bharmal, M. Real-world treatment outcomes in patients with metastatic Merkel cell carcinoma treated with chemotherapy in the USA. Future Oncol. 2017, 13, 1699–1710. [Google Scholar] [CrossRef]
  6. Hernandez, L.E.; Mohsin, N.; Yaghi, M.; Frech, F.S.; Dreyfuss, I.; Nouri, K. Merkel cell carcinoma: An updated review of pathogenesis, diagnosis, and treatment options. Dermatol. Ther. 2022, 35, e15292. [Google Scholar] [CrossRef]
  7. Iyer, J.G.; Blom, A.; Doumani, R.; Lewis, C.; Tarabadkar, E.S.; Anderson, A.; Ma, C.; Bestick, A.; Parvathaneni, U.; Bhatia, S.; et al. Response rates and durability of chemotherapy among 62 patients with metastatic Merkel cell carcinoma. Cancer Med. 2016, 5, 2294–2301. [Google Scholar] [CrossRef]
  8. D’Angelo, S.P.; Russell, J.; Lebbé, C.; Chmielowski, B.; Gambichler, T.; Grob, J.J.; Kiecker, F.; Rabinowits, G.; Terheyden, P.; Kaufman, H.L.; et al. Efficacy and Safety of First-line Avelumab Treatment in Patients with Stage IV Metastatic Merkel Cell Carcinoma: A Preplanned Interim Analysis of a Clinical Trial. JAMA Oncol. 2018, 4, e180077. [Google Scholar] [CrossRef]
  9. D’Angelo, S.P.; Bhatia, S.; Brohl, A.S.; Hamid, O.; Mehnert, J.M.; Terheyden, P.; Shih, K.C.; Brownell, I.; Lebbé, C.; Nghiem, P.T.; et al. Avelumab in patients with previously treated metastatic Merkel cell carcinoma (JAVELIN Merkel 200): Updated overall survival data after >5 years of follow-up. ESMO Open 2021, 6, 100290. [Google Scholar] [CrossRef]
  10. Kim, S.; Wuthrick, E.; Blakaj, D.; Eroglu, Z.; Verschraegen, C.; Thapa, R.; Mills, M.; Dibs, K.; Liveringhouse, C.; Russell, J.; et al. Combined nivolumab and ipilimumab with or without stereotactic body radiation therapy for advanced Merkel cell carcinoma: A randomised, open label, phase 2 trial. Lancet 2022, 400, 1008–1019. [Google Scholar] [CrossRef]
  11. Kang, C. Retifanlimab: First Approval. Drugs 2023, 83, 731–737. [Google Scholar] [CrossRef]
  12. Nghiem, P.T.; Bhatia, S.; Lipson, E.J.; Kudchadkar, R.R.; Miller, N.J.; Annamalai, L.; Berry, S.; Chartash, E.K.; Daud, A.; Fling, S.P.; et al. PD-1 Blockade with Pembrolizumab in Advanced Merkel-Cell Carcinoma. N. Engl. J. Med. 2016, 374, 2542–2552. [Google Scholar] [CrossRef]
  13. Harms, K.L.; Healy, M.A.; Nghiem, P.; Sober, A.J.; Johnson, T.M.; Bichakjian, C.K.; Wong, S.L. Analysis of Prognostic Factors from 9387 Merkel Cell Carcinoma Cases Forms the Basis for the New 8th Edition AJCC Staging System. Ann. Surg. Oncol. 2016, 23, 3564–3571. [Google Scholar] [CrossRef]
  14. Kugel, C.H., 3rd; Douglass, S.M.; Webster, M.R.; Kaur, A.; Liu, Q.; Yin, X.; Weiss, S.A.; Darvishian, F.; Al-Rohil, R.N.; Weeraratna, A.T.; et al. Age Correlates with Response to Anti-PD1, Reflecting Age-Related Differences in Intratumoral Effector and Regulatory T-Cell Populations. Clin. Cancer Res. 2018, 24, 5347–5356. [Google Scholar] [CrossRef]
  15. Joshi, K.; Atwal, D.; Ravilla, R.; Pandey, Y.; Yarlagadda, N.; Kakadia, S.; Makhoul, I.; Hutchins, L.; Mahmoud, F. Immunotherapy Outcomes in Advanced Melanoma in Relation to Age. Perm. J. 2020, 24, 19.093. [Google Scholar] [CrossRef]
  16. Jain, V.; Hwang, W.-T.; Venigalla, S.; Nead, K.T.; Lukens, J.N.; Mitchell, T.C.; Shabason, J.E. Association of Age with Efficacy of Immunotherapy in Metastatic Melanoma. Oncologist 2020, 25, e381–e385. [Google Scholar] [CrossRef]
  17. Albiges, L.; Hakimi, A.A.; Xie, W.; McKay, R.R.; Simantov, R.; Lin, X.; Lee, J.-L.; Rini, B.I.; Srinivas, S.; Bjarnason, G.A.; et al. Body Mass Index and Metastatic Renal Cell Carcinoma: Clinical and Biological Correlations. J. Clin. Oncol. 2016, 34, 3655–3663. [Google Scholar] [CrossRef]
  18. Wang, Z.; Aguilar, E.G.; Luna, J.I.; Dunai, C.; Khuat, L.T.; Le, C.T.; Mirsoian, A.; Minnar, C.M.; Stoffel, K.M.; Sturgill, I.R.; et al. Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade. Nat. Med. 2019, 25, 141–151. [Google Scholar] [CrossRef]
  19. Amin, M.B.; Greene, F.L.; Edge, S.B.; Compton, C.C.; Gershenwald, J.E.; Brookland, R.K.; Meyer, L.; Gress, D.M.; Byrd, D.R.; Winchester, D.P. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more “personalized” approach to cancer staging. CA Cancer J. Clin. 2017, 67, 93–99. [Google Scholar] [CrossRef]
  20. Lichtenstein, M.R.; Nipp, R.D.; Muzikansky, A.; Goodwin, K.; Anderson, D.; Newcomb, R.A.; Gainor, J.F. Impact of Age on Outcomes with Immunotherapy in Patients with Non-Small Cell Lung Cancer. J. Thorac. Oncol. 2019, 14, 547–552. [Google Scholar] [CrossRef]
  21. Incorvaia, L.; Dimino, A.; Algeri, L.; Brando, C.; Magrin, L.; De Luca, I.; Pedone, E.; Perez, A.; Sciacchitano, R.; Bonasera, A.; et al. Body mass index and baseline platelet count as predictive factors in Merkel cell carcinoma patients treated with avelumab. Front. Oncol. 2023, 13, 1141500. [Google Scholar] [CrossRef]
  22. Pardoll, D.M. The blockade of immune checkpoints in cancer immunotherapy. Nat. Rev. Cancer 2012, 12, 252–264. [Google Scholar] [CrossRef]
  23. Di Pietro, F.; Verkhovskaia, S.; Mastroeni, S.; Carbone, M.; Abeni, D.; Di Rocco, C.; Samà, N.; Zappalà, A.; Marchetti, P.; De Galitiis, F.; et al. Clinical Predictors of Response to Anti-PD-1 First-Line Treatment in a Single-Centre Patient Cohort: A Real-World Study. Clin. Oncol. (R Coll. Radiol.) 2022, 34, e18–e24. [Google Scholar] [CrossRef]
  24. Lenci, E.; Marcantognini, G.; Cognigni, V.; Lupi, A.; Rinaldi, S.; Cantini, L.; Fiordoliva, I.; Carloni, A.L.; Rocchi, M.; Zuccatosta, L.; et al. Tumor burden as possible biomarker of outcome in advanced NSCLC patients treated with immunotherapy: A single center, retrospective, real-world analysis. Explor. Target. Antitumor Ther. 2021, 2, 227–239. [Google Scholar] [CrossRef]
  25. Hermansen, C.K.; Donskov, F. Outcomes based on age in patients with metastatic renal cell carcinoma treated with first line targeted therapy or checkpoint immunotherapy: Older patients more prone to toxicity. J. Geriatr. Oncol. 2021, 12, 827–833. [Google Scholar] [CrossRef]
  26. Giannoula, Y.; Kroemer, G.; Pietrocola, F. Cellular senescence and the host immune system in aging and age-related disorders. Biomed. J. 2023, 46, 100581. [Google Scholar] [CrossRef]
  27. Cisneros, B.; García-Aguirre, I.; Unzueta, J.; Arrieta-Cruz, I.; González-Morales, O.; Domínguez-Larrieta, J.M.; Tamez-González, A.; Leyva-Gómez, G.; Magaña, J.J. Immune system modulation in aging: Molecular mechanisms and therapeutic targets. Front. Immunol. 2022, 13, 1059173. [Google Scholar] [CrossRef]
  28. Erbe, R.; Wang, Z.; Wu, S.; Xiu, J.; Zaidi, N.; La, J.; Tuck, D.; Fillmore, N.; Giraldo, N.A.; Topper, M.; et al. Evaluating the impact of age on immune checkpoint therapy biomarkers. Cell Rep. 2021, 36, 109599. [Google Scholar] [CrossRef]
  29. McQuade, J.L.; Daniel, C.R.; Hess, K.R.; Mak, C.; Wang, D.Y.; Rai, R.R.; Park, J.J.; Haydu, L.E.; Spencer, C.; Davies, M.A.; et al. Association of body-mass index and outcomes in patients with metastatic melanoma treated with targeted therapy, immunotherapy, or chemotherapy: A retrospective, multicohort analysis. Lancet Oncol. 2018, 19, 310–322. [Google Scholar] [CrossRef]
  30. Collet, L.; Delrieu, L.; Bouhamama, A.; Crochet, H.; Swalduz, A.; Nerot, A.; Marchal, T.; Chabaud, S.; Heudel, P.E. Association between Body Mass Index and Survival Outcome in Metastatic Cancer Patients Treated by Immunotherapy: Analysis of a French Retrospective Cohort. Cancers 2021, 13, 2200. [Google Scholar] [CrossRef]
  31. Daniels, S.R. The use of BMI in the clinical setting. Pediatrics 2009, 124 (Suppl. S1), S35–S41. [Google Scholar] [CrossRef] [PubMed]
  32. Frankel, A.E.; Deshmukh, S.; Reddy, A.; Lightcap, J.; Hayes, M.; McClellan, S.; Singh, S.; Rabideau, B.; Glover, T.G.; Roberts, B.; et al. Cancer Immune Checkpoint Inhibitor Therapy and the Gut Microbiota. Integr. Cancer Ther. 2019, 18, 1534735419846379. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Impact of age and body mass index on immunotherapy outcomes relative to the median. In this cohort, progression-free survival (PFS) was defined as the time from IMTX initiation to either progressive disease, recurrence, or death. Objective response was determined as either CR or PR from the time of IMTX initiation. Age was treated as a non-linear variable for objective response, but as a linear variable for PFS and MCC-specific survival. Body mass index (BMI), Eastern Cooperative Oncology Group (ECOG) score, gender, stage, and immunosuppression status were all accounted for. The gray shaded area indicates the confidence interval. The median age was 70, with a first and third quartile value of 64 and 75, respectively. The median BMI was 30, with a first and third quartile value of 25.9 and 32.7, respectively. Black stars have been used to indicate quartile values, with the black dotted lines representing the medians. (A) shows that patients younger or older than the median age of 70 are less likely to achieve objective responses (p = 0.04). (B) shows that age is not significantly correlated with progression-free survival (p = 0.21). (C) also shows that age is not significantly correlated with MCC-specific survival (p = 0.72). (DF) show that BMI is not significantly correlated with objective response, progression-free survival, or MCC-specific survival (p = 0.41, 0.52, and 0.78, respectively). CR = complete response; PR = partial response; IMTX = immunotherapy.
Figure 1. Impact of age and body mass index on immunotherapy outcomes relative to the median. In this cohort, progression-free survival (PFS) was defined as the time from IMTX initiation to either progressive disease, recurrence, or death. Objective response was determined as either CR or PR from the time of IMTX initiation. Age was treated as a non-linear variable for objective response, but as a linear variable for PFS and MCC-specific survival. Body mass index (BMI), Eastern Cooperative Oncology Group (ECOG) score, gender, stage, and immunosuppression status were all accounted for. The gray shaded area indicates the confidence interval. The median age was 70, with a first and third quartile value of 64 and 75, respectively. The median BMI was 30, with a first and third quartile value of 25.9 and 32.7, respectively. Black stars have been used to indicate quartile values, with the black dotted lines representing the medians. (A) shows that patients younger or older than the median age of 70 are less likely to achieve objective responses (p = 0.04). (B) shows that age is not significantly correlated with progression-free survival (p = 0.21). (C) also shows that age is not significantly correlated with MCC-specific survival (p = 0.72). (DF) show that BMI is not significantly correlated with objective response, progression-free survival, or MCC-specific survival (p = 0.41, 0.52, and 0.78, respectively). CR = complete response; PR = partial response; IMTX = immunotherapy.
Cancers 16 02480 g001
Table 1. Patient demographics and clinical status at start of immunotherapy.
Table 1. Patient demographics and clinical status at start of immunotherapy.
Variable No. %
Gender
  Female43 23.5
  Male140 76.5
Age in years
   Median = 70 (range 19–91)
  <6026 14.2
   60–7060 32.8
  70–8072 39.3
   80+ 25 13.7
BMI (kg/m2)
  Median = 30.0 (range 19.4–58.7)
  18.5–24.933 19.5
  25–29.961 36.1
  30+ 75 44.4
  Data not available14
ECOG performance status
  0114 63.7
  153 29.6
  211 6.1
  31 0.6
  Data not available4
MCPyV Oncoprotein Antibody Status
  Seropositive 91 51.1
   Seronegative 8748.9
   No data5
Stage
  III 67 36.6
  IV 116 63.4
Immunosuppression type
  Immunocompetent147 80.3
  Immunosuppressed36 19.7
BMI = body mass index; ECOG = Eastern Cooperative Oncology Group; MCPyV = Merkel cell polyomavirus.
Table 2. Associations of age and body mass index (BMI) with outcomes during immunotherapy using Cox or Fine–Grey regression model.
Table 2. Associations of age and body mass index (BMI) with outcomes during immunotherapy using Cox or Fine–Grey regression model.
UnivariableMultivariable *
PredictorOutcomeHR (95% CI) † p-Value HR (95% CI) † p-Value
Age
Objective response ‡ Non-linear 0.04 Non-linear 0.04
Progression-free survival 1.13 (0.92, 1.40) 0.24 1.14 (0.93, 1.41) 0.21
MCC-specific survival 1.06 (0.81, 1.39) 0.66 1.05 (0.80, 1.37) 0.72
Overall survival 1.15 (0.91, 1.46) 0.25 1.12 (0.88, 1.42) 0.36
BMI
Objective response 1.08 (0.91, 1.29) 0.37 1.09 (0.89, 1.33) 0.41
Progression-free survival 0.97 (0.81, 1.15) 0.70 0.95 (0.80, 1.12) 0.52
MCC-specific survival 0.99 (0.80, 1.23) 0.92 0.97 (0.79, 1.20) 0.78
Overall survival 0.99 (0.80, 1.21) 0.90 0.96 (0.79, 1.17) 0.71
BMI = body mass index; HR = hazard ratio; CI = confidence interval; ECOG = Eastern Cooperative Oncology Group. * Multivariable models include age, BMI, gender, stage, immunosuppression status, and ECOG performance status. † The hazard ratios correspond to change in event rate per 10-year increase in age or change in event rate per 5 kg/m2 increase in BMI. ‡ A non-linear relationship was detected between age and objective response, which is characterized in Figure 1.
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

Alam, R.; Fan, X.; Hippe, D.S.; Tachiki, L.M.; Gong, E.; Huynh, E.; Nghiem, P.; Park, S.Y. Lack of Clinically Significant Relationships of Age or Body Mass Index with Merkel Cell Carcinoma Immunotherapy Outcomes. Cancers 2024, 16, 2480. https://doi.org/10.3390/cancers16132480

AMA Style

Alam R, Fan X, Hippe DS, Tachiki LM, Gong E, Huynh E, Nghiem P, Park SY. Lack of Clinically Significant Relationships of Age or Body Mass Index with Merkel Cell Carcinoma Immunotherapy Outcomes. Cancers. 2024; 16(13):2480. https://doi.org/10.3390/cancers16132480

Chicago/Turabian Style

Alam, Rian, Xinyi Fan, Daniel S. Hippe, Lisa M. Tachiki, Emily Gong, Emily Huynh, Paul Nghiem, and Song Youn Park. 2024. "Lack of Clinically Significant Relationships of Age or Body Mass Index with Merkel Cell Carcinoma Immunotherapy Outcomes" Cancers 16, no. 13: 2480. https://doi.org/10.3390/cancers16132480

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