Construction and validation of an ¹⁸F-FDG-PET/CT-based prognostic model to predict progression-free survival in newly diagnosed multiple myeloma patients

References

• Fonseca R, Bergsagel P, Drach J, et al. International myeloma working group molecular classification of multiple myeloma: spotlight review. Leukemia. 2009;23:2210–2221.
   PubMed Web of Science ®Google Scholar
• Dimopoulos MA, Moreau P, Terpos E, et al. Multiple myeloma: EHA-ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up†. Ann Oncol. 2021;32:309–322. doi:10.1016/j.annonc.2020.11.014
   PubMed Web of Science ®Google Scholar
• Kyle RA, Rajkumar SV. Criteria for diagnosis, staging, risk stratification and response assessment of multiple myeloma. Leukemia. 2009;23:3–9. doi:10.1038/leu.2008.291
   PubMed Web of Science ®Google Scholar
• Greipp PR, San Miguel J, Durie BGM, et al. International staging system for multiple myeloma. J Clin Oncol. 2005;23:3412–3420. doi:10.1200/JCO.2005.04.242
   PubMed Web of Science ®Google Scholar
• Palumbo A, Avet-Loiseau H, Oliva S, et al. Revised international staging system for multiple myeloma: a report from international myeloma working group. J Clin Oncol. 2015;33:2863–2869. doi:10.1200/JCO.2015.61.2267
   PubMed Web of Science ®Google Scholar
• Kumar SK, Mikhael JR, Buadi FK, et al. Management of newly diagnosed symptomatic multiple myeloma: updated mayo stratification of myeloma and risk-adapted therapy (mSMART) consensus guidelines. Mayo Clin Proc. 2009;84:1095–1110. doi:10.4065/mcp.2009.0603
   PubMed Web of Science ®Google Scholar
• Mikhael JR, Dingli D, Roy V, et al. Management of newly diagnosed symptomatic multiple myeloma: updated mayo stratification of myeloma and risk-adapted therapy (mSMART) consensus guidelines 2013. Mayo Clin Proc. 2013;88:360–376. doi:10.1016/j.mayocp.2013.01.019
   PubMed Web of Science ®Google Scholar
• Dispenzieri A, Rajkumar SV, Gertz MA, et al. Treatment of newly diagnosed multiple myeloma based on mayo stratification of myeloma and risk-adapted therapy (mSMART): consensus statement. Mayo Clin Proc. 2007;82:323–341. doi:10.1016/S0025-6196(11)61029-X
   PubMed Web of Science ®Google Scholar
• Rajkumar SV, Dimopoulos MA, Palumbo A, et al. International myeloma working group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15:e538–e548. doi:10.1016/S1470-2045(14)70442-5
   PubMed Web of Science ®Google Scholar
• Albano D, Bosio G, Treglia G, et al. 18F-FDG PET/CT in solitary plasmacytoma: metabolic behavior and progression to multiple myeloma. Eur J Nucl Med Mol Imaging. 2018;45:77–84. doi:10.1007/s00259-017-3810-5
   PubMed Web of Science ®Google Scholar
• Agarwal A, Chirindel A, Shah BA, et al. Evolving role of FDG PET/CT in multiple myeloma imaging and management. Am J Roentgenol. 2013;200:884–890. doi:10.2214/AJR.12.9653
   PubMed Web of Science ®Google Scholar
• Cavo M, Terpos E, Nanni C, et al. Role of 18F-FDG PET/CT in the diagnosis and management of multiple myeloma and other plasma cell disorders: a consensus statement by the international myeloma working group. Lancet Oncol. 2017;18:e206–e217. doi:10.1016/S1470-2045(17)30189-4
   PubMed Web of Science ®Google Scholar
• Jung S-H, Kwon SY, Min J-J, et al. 18F-FDG PET/CT is useful for determining survival outcomes of patients with multiple myeloma classified as stage II and III with the revised international staging system. Eur J Nucl Med Mol Imaging. 2019;46:107–115. doi:10.1007/s00259-018-4114-0
   PubMed Web of Science ®Google Scholar
• Zamagni E, Patriarca F, Nanni C, et al. Prognostic relevance of 18-F FDG PET/CT in newly diagnosed multiple myeloma patients treated with up-front autologous transplantation. Blood. 2011;118:5989–5995. doi:10.1182/blood-2011-06-361386
   PubMed Web of Science ®Google Scholar
• Iasonos A, Schrag D, Raj GV, et al. How to build and interpret a nomogram for cancer prognosis. J Clin Oncol. 2008;26:1364–1370. doi:10.1200/JCO.2007.12.9791
   PubMed Web of Science ®Google Scholar
• Li Y, Liu Y, Yin P, et al. MRI-Based Bone marrow radiomics nomogram for prediction of overall survival in patients with multiple myeloma. Front Oncol. 2021;11(709813).
   Google Scholar
• Lee B-H, Park Y, Kim JH, et al. PD-L1 expression in bone marrow plasma cells as a biomarker to predict multiple myeloma prognosis: developing a nomogram-based prognostic model. Sci Rep. 2020;10(12641).
   Google Scholar
• Han S, Woo S, Kim Y-I, et al. Prognostic value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography in newly diagnosed multiple myeloma: a systematic review and meta-analysis. Eur Radiol. 2021;31:152–162. doi:10.1007/s00330-020-07177-x
   PubMed Web of Science ®Google Scholar
• Cerci JJ, Pracchia LF, Linardi CCG, et al. 18F-FDG PET after 2 cycles of ABVD predicts event-free survival in early and advanced hodgkin lymphoma. J Nucl Med. 2010;51:1337–1343. doi:10.2967/jnumed.109.073197
   PubMed Web of Science ®Google Scholar
• Lopci E, Hicks RJ, Dimitrakopoulou-Strauss A, et al. Joint EANM/SNMMI/ANZSNM practice guidelines/procedure standards on recommended use of [18F]FDG PET/CT imaging during immunomodulatory treatments in patients with solid tumors version 1.0. Eur J Nucl Med Mol Imaging. 2022;49:2323–2341. doi:10.1007/s00259-022-05780-2
   PubMed Web of Science ®Google Scholar
• Simonsson B, Brenning G, Källander C, et al. Prognostic value of serum lactic dehydrogenase (S-LDH) in multiple myeloma. Eur J Clin Invest. 1987;17:336–339. doi:10.1111/j.1365-2362.1987.tb02197.x
   PubMed Web of Science ®Google Scholar
• Cho H, Yoon DH, Lee JB, et al. Comprehensive evaluation of the revised international staging system in multiple myeloma patients treated with novel agents as a primary therapy. Am J Hematol 2017;92:1280–1286. doi:10.1002/ajh.24891
   PubMed Web of Science ®Google Scholar
• Rajkumar SV, Fonseca R, Dispenzieri A, et al. Methods for estimation of bone marrow plasma cell involvement in myeloma: predictive value for response and survival in patients undergoing autologous stem cell transplantation. Am J Hematol 2001;68:269–275. doi:10.1002/ajh.10003
   PubMed Web of Science ®Google Scholar
• Bladé J, Dimopoulos M, Rosiñol L, et al. Smoldering (asymptomatic) multiple myeloma: current diagnostic criteria, new predictors of outcome, and follow-up recommendations. J Clin Oncol. 2010;28:690–697. doi:10.1200/JCO.2009.22.2257
   PubMed Web of Science ®Google Scholar
• Rajkumar SV. Multiple myeloma update on diagnosis, risk-stratification and management. Am J Hematol. 2020;2020(95):548–567.
   Google Scholar
• Sachpekidis C, Mai EK, Goldschmidt H, et al. 18F-FDG dynamic PET/CT in patients with multiple myeloma: patterns of tracer uptake and correlation with bone marrow plasma cell infiltration rate. Clin Nucl Med. 2015;40(e300).
   PubMedGoogle Scholar
• Corre J, Perrot A, Caillot D, et al. del(17p) without TP53 mutation confers a poor prognosis in intensively treated newly diagnosed patients with multiple myeloma. Blood. 2021;137:1192–1195. doi:10.1182/blood.2020008346
   PubMed Web of Science ®Google Scholar
• D'Agostino M, Cairns DA, Lahuerta JJ, et al. Second revision of the international staging system (R2-ISS) for overall survival in multiple myeloma: a European myeloma network (EMN) report within the HARMONY project. J Clin Oncol. 2022;40:3406–3418. doi:10.1200/JCO.21.02614
   PubMed Web of Science ®Google Scholar
• Tu H, He Y, Huang T, et al. Predictive value of 18F-FDG PET/CT scanning in combination with clinical parameters in patients with newly diagnosed multiple myeloma. Eur J Haematol 2018;100:189–197. doi:10.1111/ejh.13006
   PubMed Web of Science ®Google Scholar
• Cui J, Zou Z, Duan J, et al. Predictive values of PET/CT in combination with regulatory B cells for therapeutic response and survival in contemporary patients with newly diagnosed multiple myeloma. Front Immunol. 2021;12(671904).
   Google Scholar
• Park S, Lee SJ, Chang WJ, et al. Positive correlation between baseline PET or PET/CT findings and clinical parameters in multiple myeloma patients. Acta Haematol 2014;131:193–199. doi:10.1159/000354839
   PubMed Web of Science ®Google Scholar
• Goswami C, Poonia S, Kumar L, et al. Staging system to predict the risk of relapse in multiple myeloma patients undergoing autologous stem cell transplantation. Front Oncol. 2019;9(633).
   Google Scholar
• Balachandran VP, Gonen M, Smith JJ, et al. Nomograms in oncology: more than meets the eye. The Lancet Oncol. 2015;16:e173–e180. doi:10.1016/S1470-2045(14)71116-7
   PubMed Web of Science ®Google Scholar
• Kaufman JL, Dimopoulos MA, White D, et al. Daratumumab, lenalidomide, and dexamethasone in relapsed/refractory myeloma: a cytogenetic subgroup analysis of POLLUX. Blood Cancer J. 2020;10(111).
   Google Scholar
• Terao T, Machida Y, Tsushima T, et al. Pre-treatment metabolic tumour volume and total lesion glycolysis are superior to conventional positron-emission tomography/computed tomography variables for outcome prediction in patients with newly diagnosed multiple myeloma in clinical practice. Br J Haematol 2020;191:223–230. doi:10.1111/bjh.16633
   PubMed Web of Science ®Google Scholar