To our knowledge, the present study is the first to quantify HRU and costs during recurrence episodes and in the year after recurrence (allowing the estimation of savings associated with 1 year of recurrence-free survival) in patients with nonmetastatic melanoma undergoing melanoma surgery. The matched comparison between patients with and without recurrence suggested significantly higher HRU and costs associated with recurrence, particularly distant recurrence (with melanoma treatment the main contributor to costs in the first year after recurrence). Patients with distant recurrences had 186 more OP visits per 100 person-months in the year after recurrence compared with recurrence-free patients, whereas all-cause healthcare costs were higher by $14 953 PPPM in the year after recurrence. Previous studies in real-world USA populations have reported a range of $6773–62 859 PPPM for patients with metastatic melanoma 16,20,21,44. Outside of the USA, including in developing countries, the cost per patient with melanoma was reported to range between $9162 and $86 875 14,45–47.
The wide range may be explained by these studies’ data sources, methodological differences, and various foci (notably, inclusion of patients using only certain treatments). Nevertheless, the estimate of $12 940 PPPM during episodes of distant recurrence in the current study is within the range of past studies, especially when considering real-world USA population.
The infrequent use of adjuvant therapies and the relatively high rate of postsurgery recurrences observed in this study suggest an unmet treatment need in patients with nonmetastatic melanoma undergoing surgery. Furthermore, as melanoma recurrence is associated with increased HRU and costs, strategies to prevent or delay recurrences are highly desired. The results of this study suggest that preventing a single episode of distant recurrence would lead to savings of ∼$180 000 in the year after recurrence ($14 953 PPPM); similarly, preventing a single episode of locoregional recurrence would lead to saving of ∼$10 000 in the year after recurrence ($841 per month PPPM). In the USA and Europe, adjuvant therapy for advanced melanoma is recommended or there are new indications 10–12, but the optimal treatment strategy for melanoma patients after melanoma surgery has remained elusive because of the difficult trade-off between long-term recurrence prevention and short-term toxicities with interferon and ipilimumab. However, the treatment landscape for melanoma in the adjuvant setting will soon change as results from phase 3 clinical trials of new-generation targeted agents and immune checkpoint inhibitors will offer melanoma patients additional adjuvant treatment options with demonstrated efficacy 35,48. In the COMBI-AD trial, adjuvant use of combination dabrafenib and trametenib in patients with stage III BRAF-mutated melanoma was associated with a lower risk of recurrence (37 vs. 57% in the placebo group) 35. In the CheckMate 238, a higher rate of recurrence free-survival was observed among patients treated with adjuvant nivolumab (70.5 vs. 60.8% in the placebo group) 48. Whether these new treatment options lead to consensus on the use of adjuvant therapies in patients with stage III melanoma remains to be determined.
This study was subject to common limitations of studies on the basis of healthcare claims data, including occasional coding errors or inaccurate/missing data on prescriptions, procedures, or diagnoses. Because information on recurrence is unavailable in claims databases, this study relied on an algorithm to infer recurrence and duration of recurrence episodes. Although previous studies have reported that claims-based algorithms can be used reliably to identify lines of treatment and cancer recurrences 26–28,49–51, potential misclassifications cannot be excluded. In particular, patients with recurrences who did not receive treatment or a diagnosis code for secondary malignancy were not detected. Also, despite the requirement of 12 months of insurance coverage before the first melanoma diagnosis, for some patients, the first melanoma diagnosis captured in the current study could have corresponded to a recurrence rather than the first melanoma diagnosis in the patient’s lifetime. However, the mean age of patients at first melanoma diagnosis (53.8 years) was comparable to patient characteristics reported at diagnosis in retrospective studies (i.e. 48.6–53.4 years old) 36,52, suggesting that this limitation may have limited impact. Finally, the study was a retrospective comparative analysis and may be subject to residual confounding because of unmeasured confounders.
Assistance in preparing figures and tables was provided by Ahmed Kazi and Allie Briggs, whereas medical writing assistance was provided by Sara Kaffashian and Samuel Rochette. All were employees of Analysis Group Inc.
This study was funded by Novartis Pharmaceuticals Corporation. The study sponsor was involved in all stages of the study research, including study design; collection, analysis, and interpretation of data; writing of the report; and the decision to submit the report for publication.
Analysis Group Inc. received consulting fees from Novartis Pharmaceuticals Corporation for the conduct of this study.
Ahmad Tarhini: consultant role with Novartis Pharmaceuticals Corporation. Sameer R. Ghate, Briana Ndife, and Antonio Nakasato are employees of Novartis Pharmaceuticals Corporation and may own stock/stock options. Raluca Ionescu-Ittu, Ameur M. Manceur, Philippe Jacques, François Laliberté, Rebecca Burne, and Mei Sheng Duh are employees of Analysis Group Inc., which has received consultancy fees from Novartis Pharmaceuticals Corporation
1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018; 68:7–30.
2. Karimkhani C, Green AC, Nijsten T, Weinstock MA, Dellavalle RP, Naghavi M, et al. The global burden of melanoma
: results from the Global Burden of Disease Study 2015. Br J Dermatol 2017; 177:134–140.
3. Pollack LA, Li J, Berkowitz Z, Weir HK, Wu XC, Ajani UA, et al. Melanoma
survival in the United States, 1992 to 2005. J Am Acad Dermatol 2011; 65 (Suppl 1):S78–S86.
4. Wong SL, Faries MB, Kennedy EB, Agarwala SS, Akhurst TJ, Ariyan C, et al. Sentinel lymph node biopsy and management of regional lymph nodes in melanoma
: American Society of Clinical Oncology and Society of Surgical Oncology Clinical Practice Guideline Update. J Clin Oncol 2018; 36:399–413.
5. Benvenuto-Andrade C, Oseitutu A, Agero AL, Marghoob AA. Cutaneous melanoma
: surveillance of patients for recurrence
and new primary melanomas. Dermatol Ther 2005; 18:423–435.
6. Leiter U, Meier F, Schittek B, Garbe C. The natural course of cutaneous melanoma
. J Surg Oncol 2004; 86:172–178.
7. Romano E, Scordo M, Dusza SW, Coit DG, Chapman PB. Site and timing of first relapse in stage III melanoma
patients: implications for follow-up guidelines. J Clin Oncol 2010; 28:3042.
8. Dalal KM, Patel A, Brady MS, Jaques DP, Coit DG. Patterns of first-recurrence
survival in patients with primary cutaneous melanoma
after sentinel lymph node biopsy. Ann Surg Oncol 2007; 14:1934–1942.
9. Tarhini AA. The future of systemic therapy of melanoma
: combinations, predictive biomarkers. Oncology 2015; 29:94.
10. National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology, Melanoma
2017. Version I. 2018. 11 October 2017.
13. Harlan LC, Lynch CF, Ballard-Barbash R, Zeruto C. Trends in the treatment and survival for local and regional cutaneous melanoma
in a US population-based study. Melanoma
Res 2011; 21:547–554.
14. Guy GP Jr, Ekwueme DU, Tangka FK, Richardson LC. Melanoma
treatment costs: a systematic review of the literature, 1990-2011. Am J Prev Med 2012; 43:537–545.
15. Hackshaw MD, Krishna A, Mauro DJ. Retrospective US database analysis of drug utilization patterns, health care resource use, and costs associated with adjuvant interferon alfa-2b therapy for treatment of malignant melanoma
following surgery. Clinicoecon Outcomes Res 2012; 4:169–176.
16. Chang CL, Schabert VF, Munakata J, Donga P, Abhyankar S, Reyes CM, et al. Comparative healthcare costs in patients with metastatic melanoma
in the USA. Melanoma
Res 2015; 25:312–320.
17. Harries M, Mohr P, Grange F, Ehness R, Benjamin L, Siakpere O, et al. Treatment patterns and outcomes of Stage IIIB/IIIC melanoma
in France, Germany and the UK: a retrospective and prospective observational study (MELABIS). Int J Clin Pract 2017; 71:12946.
18. Johnston K, Levy AR, Lorigan P, Maio M, Lebbe C, Middleton M, et al. Economic impact of healthcare resource utilisation patterns among patients diagnosed with advanced melanoma
in the United Kingdom, Italy, and France: results from a retrospective, longitudinal survey (MELODY study). Eur J Cancer 2012; 48:2175–2182.
19. McKendrick J, Gijsen M, Quinn C, Barber B, Zhao Z. Estimating healthcare resource use associated with the treatment of metastatic melanoma
in eight countries. J Med Econ 2016; 19:587–595.
20. Reyes C, DaCosta Byfield S, Linke R, Satram-Hoang S, Teitelbaum AH. The burden of metastatic melanoma
: treatment patterns, healthcare use (utilization), and costs. Melanoma
Res 2013; 23:159–166.
21. Toy EL, Vekeman F, Lewis MC, Oglesby AK, Duh MS. Costs, resource utilization, and treatment patterns for patients with metastatic melanoma
in a commercially insured setting. Curr Med Res Opin 2015; 31:1561–1572.
22. Warren JL, Yabroff KR. Challenges and opportunities in measuring cancer recurrence
in the United States. J Natl Cancer Inst 2015; 107:djv134.
24. Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011; 173:676–682.
25. Sarfati D, Gurney J, Stanley J, Salmond C, Crampton P, Dennett E, et al. Cancer-specific administrative data-based comorbidity indices provided valid alternative to Charlson and National Cancer Institute Indices. J Clin Epidemiol 2014; 67:586–595.
26. Hurvitz S, Guerin A, Brammer M, Guardino E, Zhou ZY, Latremouille Viau D, et al. Investigation of adverse-event-related costs for patients with metastatic breast cancer in a real-world setting. Oncologist 2014; 19:901–908.
27. Ramsey S, Henk H, Smith G, Sollano J, Chen C. First-, second- and third-line lung cancer treatment patterns and associated costs in a US healthcare claims database. Lung Cancer Manag 2015; 1:131–143.
28. Seal BS, Sullivan SD, Ramsey S, Shermock KM, Ren J, Kreilick C, et al. Medical costs associated with use of systemic therapy in adults with colorectal cancer. J Manag Care Pharm 2013; 19:461–467.
29. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 2011; 46:399–424.
30. Cohen J. Statistical power analysis for the behavioral sciences. Toronto: Academic; 1977.
31. Yang D, Dalton JE. A unified approach to measuring the effect size between two groups using SAS. SAS Global Forum 2012; 22–25 April 2012; Orlando, FL, USA.
32. Austin PC. Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research. Commun Stat Simul Comput 2009; 38:1228–1234.
33. Harder VS, Stuart EA, Anthony JC. Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research. Psychol Methods 2010; 15:234–249.
34. Stuart EA, Lee BK, Leacy FP. Prognostic score-based balance measures can be a useful diagnostic for propensity score methods in comparative effectiveness research. J Clin Epidemiol 2013; 66 (Suppl):S84–S90.e1.
35. Long GV, Hauschild A, Santinami M, Atkinson V, Mandala M, Chiarion-Sileni V, et al. Adjuvant dabrafenib plus trametinib in stage III BRAF-mutated melanoma
. N Engl J Med 2017; 377:1813–1823.
36. Salama AK, de Rosa N, Scheri RP, Pruitt SK, Herndon JE 2nd, Marcello J, et al. Hazard-rate analysis and patterns of recurrence
in early stage melanoma
: moving towards a rationally designed surveillance strategy. PLoS One 2013; 8:e57665.
37. Svedman FC, Pillas D, Taylor A, Kaur M, Linder R, Hansson J. Stage-specific survival and recurrence
in patients with cutaneous malignant melanoma
in Europe – a systematic review of the literature. Clin Epidemiol 2016; 8:109–122.
38. Eggermont AM, Suciu S, Testori A, Santinami M, Kruit WH, Marsden J, et al. Long-term results of the randomized phase III trial EORTC 18991 of adjuvant therapy
with pegylated interferon alfa-2b versus observation in resected stage III melanoma
. J Clin Oncol 2012; 30:3810–3818.
39. Garbe C, Radny P, Linse R, Dummer R, Gutzmer R, Ulrich J, et al. Adjuvant low-dose interferon α2a with or without dacarbazine compared with surgery alone: a prospective-randomized phase III DeCOG trial in melanoma
patients with regional lymph node metastasis. Ann Oncol 2008; 19:1195–1201.
40. Vazquez Vde L, Silva TB, Vieira Mde A, de Oliveira AT, Lisboa MV, de Andrade DA, et al. Melanoma
characteristics in Brazil: demographics, treatment, and survival analysis. BMC Res Notes 2015; 8:4.
41. Lens M. Cutaneous melanoma
: interferon alpha adjuvant therapy
for patients at high risk for recurrent disease. Dermatol Ther 2006; 19:9–18.
42. Petrella T, Verma S, Spithoff K, Quirt I, McCready D. Adjuvant interferon therapy for patients at high risk for recurrent melanoma
: an updated systematic review and practice guideline. Clin Oncol (R Coll Radiol) 2012; 24:413–423.
43. Zhang Y, Le TK, Shaw JW, Kotapati S. Retrospective analysis of drug utilization, health care resource use, and costs associated with IFN therapy for adjuvant treatment of malignant melanoma
. Clinicoecon Outcomes Res 2015; 7:397–407.
44. Vekeman F, Cloutier M, Yermakov S, Amonkar MM, Arondekar B, Duh MS. Economic burden
of brain metastases among patients with metastatic melanoma
in a USA managed care population. Melanoma
Res 2014; 24:602–610.
45. Souza RJ, Mattedi AP, Corrêa MP, Rezende ML, Ferreira AC. Estimativa do custo do tratamento do câncer de pele tipo não-melanoma
no Estado de São Paulo – Brasil [Estimation of the cost of non-melanoma
skin cancer treatment in Sao Paulo – Brazil]. An Bras Dermatol 2011; 86:657–662.
46. Almazán-Fernández FM, Serrano-Ortega S, Moreno-Villalonga JJ. Descriptive study of the costs of diagnosis and treatment of cutaneous melanoma
. Actas Dermosifiliogr 2009; 100:785–791.
47. Leiter U, Marghoob AA, Lasithiotakis K, Eigentler TK, Meier F, Meisner C, et al. Costs of the detection of metastases and follow-up examinations in cutaneous melanoma
Res 2009; 19:50–57.
48. Weber J, Mandala M, Del Vecchio M, Gogas HJ, Arance AM, Cowey CL, et al. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma
. N Engl J Med 2017; 377:1824–1835.
49. Chubak J, Yu O, Pocobelli G, Lamerato L, Webster J, Prout MN, et al. Administrative data algorithms to identify second breast cancer events following early-stage invasive breast cancer. J Natl Cancer Inst 2012; 104:931–940.
50. Deshpande AD, Schootman M, Mayer A. Development of a claims-based algorithm to identify colorectal cancer recurrence
. Ann Epidemiol 2015; 25:297–300.
51. Livaudais-Toman J, Egorova N, Franco R, Prasad-Hayes M, Howell EA, Wisnivesky J, et al. A validation study of administrative claims data to measure ovarian cancer recurrence
and secondary debulking surgery. EGEMS 2016; 4:1208.
52. Dong XD, Tyler D, Johnson JL, DeMatos P, Seigler HF. Analysis of prognosis and disease progression after local recurrence
. Cancer 2000; 88:1063–1071.