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Patterns and Drivers of Costs for Neuroendocrine Tumor Care: A Comparative Population-Based Analysis

  • Endocrine Tumors
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

Little is known about resource use in the care of neuroendocrine tumors (NETs). This study defined patterns of costs in NET management and compared them with those of a more common malignancy, colon cancer (CC).

Methods

Using a provincial cancer registry (2004–2012), NET patients were identified and matched at a ratio of 1–3 with CC patients. Four phases of care were examined: pre-diagnostic (PreDx: −2 years to −181 days), diagnostic (Dx: −180 days to +180 days), postdiagnostic (PostDx: +181 days to +3 years), and prolonged post-diagnostic (PPostDx: +181 days to +9 years). The mean costs per patient were compared, and cost predictors were analyzed with quintile regression.

Results

Of 3827 NETs, 3355 were matched with 9320 CCs. The PreDx mean NET costs were higher than the CC costs ($5877 vs $5368; p = 0.06), driven by nondrug costs. They were lower in the Dx and PostDx phases (both p < 0.01). For PPostDx, the drug costs were higher for NETs ($26,788 vs $7827; p < 0.01), representing 41% of the costs versus 16% of the costs for CC. Older age and comorbidities predicted higher NET costs in all phases. Lower socioeconomic status (SES) predicted higher costs in the initial phases and higher SES costs in the PPost-Dx phase. Gastroenteric NETs were associated with lower costs in the Dx phase [parameter estimate (PE), −$13,644] and pancreatic NETs with higher costs in PostDx phase (PE, $3348).

Conclusion

Currently, NETs represent a potential important health care burden. The NET cost patterns differed from those for CC, with the highest costs during the PPostDx phase. The SES and primary NET site affected costs differently at different time points. These data can inform resource allocation tailored to the needs for NETs.

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References

  1. Modlin IM, Kidd M, Latich I, et al. Current status of gastrointestinal carcinoids. Gastroenterology. 2005;128:1717–51.

    Article  PubMed  Google Scholar 

  2. Hallet J, Law CHL, Cukier M, et al. Exploring the rising incidence of neuroendocrine tumors: a population-based analysis of epidemiology, metastatic presentation, and outcomes. Cancer. 2015;121:589–97.

    Article  PubMed  Google Scholar 

  3. Yao JC, Hassan M, Phan A, et al. One hundred years after “carcinoid”: epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J Clin Oncol. 2008;26:3063–72.

    Article  PubMed  Google Scholar 

  4. Modlin IM, Lye KD, Kidd M. A 5-decade analysis of 13,715 carcinoid tumors. Cancer. 2003;97:934–59.

    Article  PubMed  Google Scholar 

  5. Hauso O, Gustafsson BI, Kidd M, et al. Neuroendocrine tumor epidemiology (Internet). Cancer. 2008;113:2655–64. doi:10.1002/cncr.23883.

    Article  PubMed  Google Scholar 

  6. Modlin IM, Moss SF, Chung DC, et al. Priorities for improving the management of gastroenteropancreatic neuroendocrine tumors. J Natl Cancer Inst. 2008;100:1282–9.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Fraenkel M, Kim MK, Faggiano A, et al. Epidemiology of gastroenteropancreatic neuroendocrine tumours. Best Pract Res Clin Gastroenterol. 2012;26:691–703.

    Article  CAS  PubMed  Google Scholar 

  8. Benchimol EI, Smeeth L, Guttmann A, et al. The reporting of studies conducted using Observational Routinely Collected Health Data (RECORD) Statement. PLoS Med. 2015;12:e1001885.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Robles SC, Marrett LD, Clarke EA, et al. An application of capture-recapture methods to the estimation of completeness of cancer registration (Internet). J Clin Epidemiol. 1988;41:495–501.

  10. Clarke EA, Marrett LD, Kreiger N. Cancer registration in Ontario: a computer approach (Internet). IARC Sci Publ. 1991;95:246–57.

  11. Holowaty EJ, Dale D. The hospital-only project. Health Rep. 1993;5:91–95.

    CAS  PubMed  Google Scholar 

  12. Paszat L, Brundage M, Groome PA, et al. A population-based study of rectal cancer: permanent colostomy as an outcome. Int J Radiat Oncol. 1999;45:1185–91.

    Article  CAS  Google Scholar 

  13. Juurlink DN, Preyra C, Croxford R, et al. Canadian Institute for Health Information Discharge Abstract Database: a validation study, Institute for Clinical Evaluative Sciences, Toronto, 2006.

    Google Scholar 

  14. Quan H, Parsons GA, Ghali WA. Validity of information on comorbidity derived rom ICD-9-CCM administrative data. Med Care. 2002;40:675–85.

    Article  PubMed  Google Scholar 

  15. Canadian Institute for Health Information. Canadian Institute for Health Information, CIHI Data Quality Study of Ontario Emergency Department Visits for Fiscal Year 2004–2005. Ottawa, 2008.

  16. Wodchis WP, Naglie G, Teare GF. Validating diagnostic information on the minimum data set in Ontario hospital-based long-term care. Med Care. 2008;46:882–7.

    Article  PubMed  Google Scholar 

  17. Williams J, Young W. Appendix: A Summary of Studies on the Quality of Health Care Administrative Databases in Canada. In: Williams VG, Anderson JL, Blackstein-Hirsh GM, et al (eds). Patterns of health care in Ontario. Ottawa: Canadian Medical Association, 1996.

    Google Scholar 

  18. Levy AR, O’Brien BJ, Sellors C, et al. Coding accuracy of administrative drug claims in the Ontario Drug Benefit database. Can J Clin Pharmacol. 2003;10:67–71.

    PubMed  Google Scholar 

  19. Liu N, Mittmann N, Coyte PC, et al. Phase-specific health care costs of cervical cancer: estimates from a population-based study. Am J Obstet Gynecol. 2016;214:615.e1–e11.

    Google Scholar 

  20. Mittmann N, Porter JM, Rangrej J, et al. Health system costs for stage-specific breast cancer: a population-based approach. Curr Oncol. 2014;21:281.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Cheung MC, Earle CC, Rangrej J, et al. Impact of aggressive management and palliative care on cancer costs in the final month of life. Cancer. 2015;121:3307–15.

    Article  PubMed  PubMed Central  Google Scholar 

  22. World Health Organization. International Classification of Diseases for Oncology (ICD-O). Geneva: WHO; 1976.

    Google Scholar 

  23. Wilkins R. Use of postal codes and addresses in the analysis of health data. Health Rep. 1993;5:157–77.

    CAS  PubMed  Google Scholar 

  24. Alter DA, Naylor CD, Austin P, et al. Effects of socioeconomic status on access to invasive cardiac procedures and on mortality after acute myocardial infarction. N Engl J Med. 1999;341:1359–67.

    Article  CAS  PubMed  Google Scholar 

  25. Plessis Du V, Beshiri R, Bollman R. Definitions of “rural:” rural small-town Canada. Anal Bull. 2013;3:1–43.

    Google Scholar 

  26. Chau I, Casciano R, Willet J, et al. Quality of life, resource utilisation and health economics assessment in advanced neuroendocrine tumours: a systematic review. Eur J Cancer Care. 2013;22:714–25.

    Article  CAS  Google Scholar 

  27. Spolverato G, Vitale A, Ejaz A, et al. Net health benefit of hepatic resection versus intraarterial therapies for neuroendocrine liver metastases: a Markov decision model. Surgery. 2015;158:339–48.

    Article  PubMed  Google Scholar 

  28. Dimitroulopoulos D, Xynopoulos D, Tsamakidis K, et al. Scintigraphic detection of carcinoid tumors with a cost effectiveness analysis. WJG. 2004;10:3628–33.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Broder MS, Chang E, Romanus D, et al. Healthcare and economic impact of diarrhea in patients with carcinoid syndrome. WJG. 2016;22:2118–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Orlewska E, Bednarczuk T, Kaminski G, et al. LanroNET, a non-interventional, prospective study to assess the resource utilization and cost of lanreotide autogel 120 mg in Polish patients with neuroendocrine tumors: results of interim analysis. Contemp Oncol Pozn. 2014;18:442–7.

    PubMed  PubMed Central  Google Scholar 

  31. Casciano R, Wang X, Stern L, et al. International practice patterns and resource utilization in the treatment of neuroendocrine tumors. Pancreas. 2013;42:339–47.

    Article  PubMed  Google Scholar 

  32. Chuang C-C, Bhurke S, Chen S-Y, et al. (2014) Clinical characteristics, treatment patterns, and economic burden in patients treated for neuroendocrine tumors in the United States: a retrospective cohort study. J Med Econ. doi:10.3111/13696998.2014.975233.

    PubMed  Google Scholar 

  33. Institute for Clinical Evaluative Sciences (ICES) (Internet). http://www.ices.on.ca/index.html. Accessed January 2014.

  34. Rinke A, Müller H-H, Schade-Brittinger C, et al. Placebo-controlled, double-blind, prospective, randomized study on the effect of octreotide LAR in the control of tumor growth in patients with metastatic neuroendocrine midgut tumors: a report from the PROMID Study Group. J Clin Oncol. 2009;27:4656–63.

    Article  CAS  PubMed  Google Scholar 

  35. Yao JC, Phan AT, Chang DZ, et al. Efficacy of RAD001 (everolimus) and octreotide LAR in advanced low- to intermediate-grade neuroendocrine tumors: results of a phase II study. J Clin Oncol. 2008;26:4311–8.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Modlin IM, Oberg K, Chung DC, et al. Gastroenteropancreatic neuroendocrine tumours. Lancet Oncol. 2008;9:61–72.

    Article  CAS  PubMed  Google Scholar 

  37. Feinberg Y, Law C, Singh S, et al. Patient experiences of having a neuroendocrine tumour: a qualitative study. Eur J Oncol Nurs. 2013;17:541–5.

    Article  CAS  PubMed  Google Scholar 

  38. Caplin ME, Pavel M, Ćwikła JB, et al. Lanreotide in metastatic enteropancreatic neuroendocrine tumors. N Engl J Med. 2014;371:224–33.

    Article  PubMed  Google Scholar 

  39. Yao JC, Fazio N, Singh S, et al. Everolimus for the treatment of advanced, non-functional neuroendocrine tumours of the lung or gastrointestinal tract (RADIANT-4): a randomised, placebo-controlled, phase 3 study. Lancet. 2016;387:968–77.

    Article  CAS  PubMed  Google Scholar 

  40. Hallet J, Singh S, Law CHL. Healthcare utilization in the pre-diagnostic period for neuroendocrine tumors. Ann Surg Oncol. 2014;21:S97.

    Google Scholar 

  41. Terashima M, Rainham D, Levy AR. A small-area analysis of inequalities in chronic disease prevalence across urban and non-urban communities in the Province of Nova Scotia, Canada, 2007–2011. BMJ Open. 2014;4:e004459.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Booth CM, Li G, Zhang-Salomons J, et al. The impact of socioeconomic status on stage of cancer at diagnosis and survival: a population-based study in Ontario, Canada. Cancer. 2010;116:4160–7.

    Article  PubMed  Google Scholar 

Download references

Acknowledgement

This study was supported by the Institute for Clinical Evaluative Sciences (ICES), which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). The opinions, results, and conclusions reported in this paper are those of the authors and independent from the funding sources. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. Parts of this material are based on data and information compiled and provided by CIHI. However, the analyses, conclusions, opinions, and statements expressed in this report are those of the author and not necessarily those of CIHI. Parts of this material are based on data and information provided by Cancer Care Ontario (CCO). The opinions, results, view, and conclusions reported in this report are those of the authors and do not necessarily reflect those of CCO. No endorsement by CCO is intended or should be inferred. This work was supported by an unrestricted operating grant from the Ontario Institute for Cancer Research (no grant number is applicable).

Disclosure

There are no conflicts of interest.

Author information

Authors and Affiliations

  1. Department of Surgery, University of Toronto, Toronto, ON, Canada

    Julie Hallet MD, MSc(c), FRCSC & C. H. L. Law MD, MPH, FRCSC

  2. Division of General Surgery, Sunnybrook Health Sciences Centre – Odette Cancer Centre, Toronto, ON, Canada

    Julie Hallet MD, MSc(c), FRCSC & C. H. L. Law MD, MPH, FRCSC

  3. Sunnybrook Research Institute, Toronto, ON, Canada

    Julie Hallet MD, MSc(c), FRCSC, C. H. L. Law MD, MPH, FRCSC, M. Cheung MD, MPH, FRCSC, N. Mittmann MSc, PhD & S. Singh MD, MPH, FRCPC

  4. Institute for Clinical Evaluative Sciences, Toronto, ON, Canada

    Julie Hallet MD, MSc(c), FRCSC, N. Liu MSc, H. D. Fischer MD, MSc & S. Singh MD, MPH, FRCPC

  5. Department of Medicine, University of Toronto, Toronto, ON, Canada

    M. Cheung MD, MPH, FRCSC & S. Singh MD, MPH, FRCPC

  6. Division of Medical Oncology, Sunnybrook Health Sciences Centre – Odette Cancer Centre, Toronto, ON, Canada

    M. Cheung MD, MPH, FRCSC & S. Singh MD, MPH, FRCPC

Authors
  1. Julie Hallet MD, MSc(c), FRCSC
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  2. C. H. L. Law MD, MPH, FRCSC
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  3. M. Cheung MD, MPH, FRCSC
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  5. N. Liu MSc
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  6. H. D. Fischer MD, MSc
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  7. S. Singh MD, MPH, FRCPC
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Correspondence to Julie Hallet MD, MSc(c), FRCSC.

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Appendix: List of ICD-9 and ICD-O Codes Used for Inclusion and Exclusion Criteria

Appendix: List of ICD-9 and ICD-O Codes Used for Inclusion and Exclusion Criteria

Neuroendocrine tumor (NET) diagnosis was defined using ICD-9 code and the first four digits of the ICD-O code, as abstracted in the Ontario Cancer Registry (OCR). The population was defined using either of the criteria.

Inclusion criteria

ICD-9 codes

259.2

Carcinoid syndrome

209.20

Malignant carcinoid primary site unknown

209.25

Malignant carcinoid foregut NOS

209.26

Malignant carcinoid midgut NOS

209.27

Malignant carcinoid hindgut NOS

209.29

Malignant carcinoid other site

209.60

Benign carcinoid primary site unknown

209.65

Benign carcinoid foregut NOS

209.66

Benign carcinoid midgut NOS

209.67

Benign carcinoid hindgut NOS

209.69

Benign carcinoid other site

209.29

Malignant carcinoid of other sites

209.3

Malignant poorly differentiated neuroendocrine carcinoma

209.30

Malignant poorly differentiated neuroendocrine carcinoma, any site

209.21

Malignant carcinoid bronchus/lung

209.22

Malignant carcinoid thymus

209.62

Benign carcinoid bronchus/lung

209.61

Benign carcinoid thymus

157.4

Islets of Langerhans, any part of the pancreas

211.7

Benign neoplasm of islets of Langerhans

209.23

Malignant carcinoid stomach

209.63

Benign carcinoid stomach

209.00

Malignant carcinoid small intestine NOS

209.01

Malignant carcinoid duodenum

209.02

Malignant carcinoid jejunum

209.03

Malignant carcinoid ileum

209.40

Benign carcinoid small intestine NOS

209.41

Benign carcinoid duodenum

209.42

Benign carcinoid jejunum

209.43

Benign carcinoid ileum

209.4

Benign carcinoid of the small intestine

209.12

Malignant carcinoid appendix

209.0

Malignant carcinoid tumours of the appendix, large intestine and rectum

209.10

Malignant carcinoid large intestine NOS

209.12

Malignant carcinoid cecum

209.13

Malignant carcinoid ascending colon

209.14

Malignant carcinoid transverse colon

209.15

Malignant carcinoid descending colon

209.16

Malignant carcinoid sigmoid colon

209.17

Malignant carcinoid rectum

209.24

Malignant carcinoid kidney

ICD-O codes

8150

Islet cell carcinoma

8151

Insulinoma

8152

Glucagonoma

8153

Gastrinoma

8154

Mixed islet-cell/exocrine adenocarcinoma

8155

VIPoma

8156

Somatostatinoma

8157

Enteroglucagonoma

8240

Carcinoid

8241

Enterochromaffin cell carcinoid

8242

Enterochromaffin-like cell tumours

8244

Composite carcinoid

8245

Adenocarcinoid

8246

Neuroendocrine carcinoma

8249

Atypical carcinoid

Exclusion criteria

ICD-O codes

8002

Malignant tumour, small cell type

8040

Tumorlet

8041

Small cell carcinoma NOS

8042

Oat Cell carcinoma

8043

Small cell carcinoma NOS, fusiform cell type

8044

Small cell carcinoma NOS

8045

Combined small cell carcinoma

8013

Large cell neuroendocrine carcinoma of the lung

8700

Pheochromocytoma

8680

Paraganglioma

8693

Extra-adrenal paraganglioma

8510

Medullary carcinoma of the thyroid

8000

Neoplasm

8010

Epithelial tumor

8070

Squamous cell carcinoma

8140

Adenoma

8341

Papillary carcinoma

8481

Mucinous adenocarcinoma

8500

Ductal carcinoma

9364

Peripheral neuroectodermal tumor

9370

Chordoma

9990

No microscopic neoplasm

8243

Goblet cell carcinoid

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Hallet, J., Law, C.H.L., Cheung, M. et al. Patterns and Drivers of Costs for Neuroendocrine Tumor Care: A Comparative Population-Based Analysis. Ann Surg Oncol 24, 3312–3323 (2017). https://doi.org/10.1245/s10434-017-5986-0

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