Top

Published in:

01-04-2022 | Magnetic Resonance Imaging | Gastrointestinal

Additional MRI for initial M-staging in pancreatic cancer: a cost-effectiveness analysis

Authors: Felix G. Gassert, Sebastian Ziegelmayer, Johanna Luitjens, Florian T. Gassert, Fabian Tollens, Johann Rink, Marcus R. Makowski, Johannes Rübenthaler, Matthias F. Froelich

Published in: European Radiology | Issue 4/2022

Abstract

Objective

Pancreatic cancer is portrayed to become the second leading cause of cancer-related death within the next years. Potentially complicating surgical resection emphasizes the importance of an accurate TNM classification. In particular, the failure to detect features for non-resectability has profound consequences on patient outcomes and economic costs due to incorrect indication for resection. In the detection of liver metastases, contrast-enhanced MRI showed high sensitivity and specificity; however, the cost-effectiveness compared to the standard of care imaging remains unclear. The aim of this study was to analyze whether additional MRI of the liver is a cost-effective approach compared to routinely acquired contrast-enhanced computed tomography (CE-CT) in the initial staging of pancreatic cancer.

Methods

A decision model based on Markov simulation was developed to estimate the quality-adjusted life-years (QALYs) and lifetime costs of the diagnostic modalities. Model input parameters were assessed based on evidence from recent literature. The willingness-to-pay (WTP) was set to $100,000/QALY. To evaluate model uncertainty, deterministic and probabilistic sensitivity analyses were performed.

Results

In the base-case analysis, the model yielded a total cost of $185,597 and an effectiveness of 2.347 QALYs for CE-MR/CT and $187,601 and 2.337 QALYs for CE-CT respectively. With a net monetary benefit (NMB) of $49,133, CE-MR/CT is shown to be dominant over CE-CT with a NMB of $46,117. Deterministic and probabilistic survival analysis showed model robustness for varying input parameters.

Conclusion

Based on our results, combined CE-MR/CT can be regarded as a cost-effective imaging strategy for the staging of pancreatic cancer.

Key Points

• Additional MRI of the liver for initial staging of pancreatic cancer results in lower total costs and higher effectiveness.

• The economic model showed high robustness for varying input parameters.

Rawla P, Sunkara T, Gaduputi V (2019) Epidemiology of pancreatic cancer: global trends, etiology and risk factors. World J Oncol 10:10–27. https://doi.org/10.14740/wjon1166CrossRefPubMedPubMedCentral

Howlader N, Noone AM, Krapcho M et al (2020) SEER Cancer Statistics Review, 1975-2018, National Cancer Institute. Bethesda, MD, https://seer.cancer.gov/csr/1975_2018/, based on November 2020 SEER data submission

da Costa WL, Oluyomi AO, Thrift AP (2020) Trends in the incidence of pancreatic adenocarcinoma in all 50 United States Examined Through An Age-Period-Cohort Analysis. JNCI Cancer Spectr 4:1–7. https://doi.org/10.1093/jncics/pkaa033CrossRef

Pugalenthi A, Protic M, Gonen M et al (2016) Postoperative complications and overall survival after pancreaticoduodenectomy for pancreatic ductal adenocarcinoma. J Surg Oncol 113:188–193. https://doi.org/10.1002/jso.24125CrossRefPubMed

Glasgow RE, Jackson HH, Neumayer L et al (2007) Pancreatic resection in veterans affairs and selected university medical centers: results of the patient safety in surgery study. J Am Coll Surg 204:1252–1260. https://doi.org/10.1016/j.jamcollsurg.2007.03.015CrossRefPubMed

Conroy T, Hammel P, Hebbar M et al (2018) FOLFIRINOX or gemcitabine as adjuvant therapy for pancreatic cancer. N Engl J Med 379:2395–2406. https://doi.org/10.1056/NEJMoa1809775CrossRefPubMed

Conroy T, Desseigne F, Ychou M, et al (2011) FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N Engl J Med 1817–1825. https://doi.org/10.1056/NEJMoa1011923

Hess KR, Varadhachary GR, Taylor SH et al (2006) Metastatic patterns in adenocarcinoma. Cancer 106:1624–1633. https://doi.org/10.1002/cncr.21778CrossRefPubMed

Zhang YJ, Huang J, Chen MS, Jiao LR (2012) Preoperative vascular evaluation with computed tomography and magnetic resonance imaging for pancreatic cancer: a meta-analysis. Pancreatology 12:227–233. https://doi.org/10.1016/j.pan.2012.03.057CrossRefPubMed

10.

Motosugi U, Ichikawa T, Morisaka H et al (2011) Detection of pancreatic carcinoma and liver metastases with gadoxetic acid-enhanced MR imaging: comparison with contrast-enhanced multi-detector row CT. Radiology 260:446–453. https://doi.org/10.1148/radiol.11103548CrossRefPubMed

11.

Mao Y, Chen B, Wang H et al (2020) Diagnostic performance of magnetic resonance imaging for colorectal liver metastasis: a systematic review and meta-analysis. Sci Rep 10:1–12. https://doi.org/10.1038/s41598-020-58855-1CrossRef

12.

Kim YK, Park G, Kim CS, Yu HC, Han MY (2012) Diagnostic efficacy of gadoxetic acid-enhanced MRI for the detection and characterisation of liver metastases: comparison with multidetector-row CT. Br J Radiol 85:539–547. https://doi.org/10.1259/bjr/25139667

13.

Kim HJ, Park MS, Lee JY et al (2019) Incremental role of pancreatic magnetic resonance imaging after staging computed tomography to evaluate patients with pancreatic ductal adenocarcinoma. Cancer Res Treat 51:24–33. https://doi.org/10.4143/crt.2017.404CrossRefPubMed

14.

Arias E, Xu J (2020) United States Life Tables, 2018. Natl Vital Stat Rep 69:1–45PubMed

15.

Kachare SD, Liner KR, Vohra NA, Zervos EE, Hickey T, Fitzgerald TL (2015) Assessment of health care cost for complex surgical patients: review of cost, re-imbursement and revenue involved in pancreatic surgery at a high-volume academic medical centre. HPB (Oxford) 17:311–317. https://doi.org/10.1111/hpb.12349

16.

Sutton JM, Wilson GC, Paquette IM et al (2014) Cost effectiveness after a pancreaticoduodenectomy: bolstering the volume argument. HPB (Oxford) 16:1056–1061. https://doi.org/10.1111/hpb.12309

17.

Tramontano AC, Chen Y, Watson TR et al (2019) Pancreatic cancer treatment costs, including patient liability, by phase of care and treatment modality, 2000–2013. Medicine (Baltimore) 98(49):e18082. https://doi.org/10.1097/MD.0000000000018082CrossRef

18.

Howlader N, Noone A, Krapcho M, et al SEER Cancer Statistics Review, 1975–2017, National Cancer Institute. Bethesda, MD, https://seer.cancer.gov/csr/1975_2017/, based on November 2019 SEER data submission, posted to the SEER web site, April 2020

19.

Suh CH, Kim, KW, Park SH, et al (2018) Performing gadoxetic acid–enhanced MRI after CT for guiding curative treatment of early-stage hepatocellular carcinoma: a cost-effectiveness analysis. AJR Am J Roentgenol 210(2):W63–W69

20.

O’Neill CB, Atoria CL, O’Reilly EM, LaFemina J, Henman MC, Elkin EB (2012) Costs and trends in pancreatic cancer treatment. Cancer 118:5132–5139. https://doi.org/10.1002/cncr.27490

21.

Pezzilli R, Falconi M, Zerbi A et al (2011) Clinical and patient-reported outcomes after pancreatoduodenectomy for different diseases: a follow-up study. Pancreas 40:938–945. https://doi.org/10.1097/MPA.0b013e318216f693CrossRefPubMed

22.

Huang J, Yeo C, Sohn T et al (2000) Quality of life and outcomes after pancreaticoduodenectomy. Ann Surg 231:890–898CrossRefPubMedPubMedCentral

23.

Carrato A, Falcone A, Ducreux M et al (2015) A systematic review of the burden of pancreatic cancer in Europe: real-world impact on survival, quality of life and costs. J Gastrointest Cancer 46:201–211. https://doi.org/10.1007/s12029-015-9724-1CrossRefPubMedPubMedCentral

24.

Strobel O, Hank T, Hinz U et al (2017) Pancreatic cancer surgery. Ann Surg 265:565–573. https://doi.org/10.1097/SLA.0000000000001731CrossRefPubMed

25.

Kovač JD, Mayer P, Hackert T, Klauss M (2019) The time to and type of pancreatic cancer recurrence after surgical resection: is prediction possible? Acad Radiol 26:775–781. https://doi.org/10.1016/j.acra.2018.07.025CrossRefPubMed

26.

Sanders GD, Neumann PJ, Basu A et al (2016) Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA 316:1093–1103. https://doi.org/10.1001/jama.2016.12195

27.

Cameron D, Ubels J, Norström F (2018) On what basis are medical cost-effectiveness thresholds set? Clashing opinions and an absence of data: a systematic review. Glob Health Action 11(1):1447828. https://doi.org/10.1080/16549716.2018.1447828CrossRefPubMedPubMedCentral

28.

Toft J, Hadden WJ, Laurence JM et al (2017) Imaging modalities in the diagnosis of pancreatic adenocarcinoma: a systematic review and meta-analysis of sensitivity, specificity and diagnostic accuracy. Eur J Radiol 92:17–23. https://doi.org/10.1016/j.ejrad.2017.04.009CrossRefPubMed

29.

Bipat S, Saffire SKS, Van Delden OM et al (2005) Ultrasonography, computed tomography and magnetic resonance imaging for diagnosis and determining resectability of pancreatic adenocarcinoma: a meta-analysis. J Comput Assist Tomogr 29:438–445. https://doi.org/10.1097/01.rct.0000164513.23407.b3CrossRefPubMed

30.

McMahon PM, Halpern EF, Fernandez-del Castillo C, Clark JW, Gazelle GS (2001) Pancreatic cancer: cost-effectiveness of imaging technologies for assessing resectability. Radiology 221:93–106. https://doi.org/10.1148/radiol.2211001656

31.

Parikh T, Drew SJ, Lee VS et al (2008) Focal liver lesion detection and characterization with diffusion-weighted MR imaging: comparison with standard breath-hold T2-weighted imaging. Radiology 246:812–822. https://doi.org/10.1148/radiol.2463070432CrossRefPubMed

32.

Muhi A, Ichikawa T, Motosugi U et al (2011) Diagnosis of colorectal hepatic metastases: comparison of contrast-enhanced CT, contrast-enhanced US, superparamagnetic iron oxide-enhanced MRI, and gadoxetic acid-enhanced MRI. J Magn Reson Imaging 34:326–335. https://doi.org/10.1002/jmri.22613CrossRefPubMed

33.

Heinrich S, Goerres GW, Schäfer M et al (2005) Positron emission tomography/computed tomography influences on the management of resectable pancreatic cancer and its cost-effectiveness. Ann Surg 242:235–243. https://doi.org/10.1097/01.sla.0000172095.97787.84CrossRefPubMedPubMedCentral

34.

Saing S, Haywood P, Duncan JK, Ma N, Cameron AL, Goodall S (2018) Cost-effective imaging for resectability of liver lesions in colorectal cancer: an economic decision model. ANZ J Surg 88:E507–E511. https://doi.org/10.1111/ans.14194

35.

Shiroiw T, Sung Y-K, Fukuda T, Lang H-C, Bae S-C, Tsutani K (2010) International survey on willingness-to-pay (WTP) for one additional QALY gained: what is the threshold of cost effectiveness? Health Econ. https://doi.org/10.1002/hec.1481

36.

Gassert FG, Rübenthaler J, Cyran CC et al (2021) 18F FDG PET/MRI with hepatocyte-specific contrast agent for M staging of rectal cancer: a primary economic evaluation. Eur J Nucl Med Mol Imaging 48(10):3268-3276. https://doi.org/10.1007/s00259-021-05193-7

37.

Schnitzer ML, Froelich MF, Gassert FG et al (2020) Contrast-enhanced CT after ablation of liver metastases of colorectal carcinoma — a cost-effectiveness analysis. Cancers (Basel). https://doi.org/10.3390/cancers12092432CrossRef

Title: Additional MRI for initial M-staging in pancreatic cancer: a cost-effectiveness analysis
Authors: Felix G. Gassert
Sebastian Ziegelmayer
Johanna Luitjens
Florian T. Gassert
Fabian Tollens
Johann Rink
Marcus R. Makowski
Johannes Rübenthaler
Matthias F. Froelich
Publication date: 01-04-2022
Publisher: Springer Berlin Heidelberg
Keywords: Magnetic Resonance Imaging
Magnetic Resonance Imaging
Computed Tomography
Metastasis
Computed Tomography
Pancreatic Cancer
Pancreatic Cancer
Published in: European Radiology / Issue 4/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-021-08356-0

2024 ASCO Annual Meeting

Springer Medicine

Additional MRI for initial M-staging in pancreatic cancer: a cost-effectiveness analysis

Abstract

Objective

Methods

Results

Conclusion

Key Points

2024 ASCO Annual Meeting

Springer Medicine

Abstract

Objective

Methods

Results

Conclusion

Key Points

Please log in to get access to this content

Other articles of this Issue 4/2022

Imaging evaluation of uterine arteries in potential living donors for uterus transplantation: a comparative study of MRA, CTA, and DSA

Multimodality MRI-based radiomics approach to predict the posttreatment response of lung cancer brain metastases to gamma knife radiosurgery

Histogram analysis of diffusion-weighted imaging and dynamic contrast-enhanced MRI for predicting occult lymph node metastasis in early-stage oral tongue squamous cell carcinoma

Correlation between left ventricular fractal dimension and impaired strain assessed by cardiac MRI feature tracking in patients with left ventricular noncompaction and normal left ventricular ejection fraction

Radiomics model based on shear-wave elastography in the assessment of axillary lymph node status in early-stage breast cancer

Correction to: Prediction for pathological and immunohistochemical characteristics of triple‑negative invasive breast carcinomas: the performance comparison between quantitative and qualitative sonographic feature analysis