Decreased psoas muscle area is a prognosticator for 90-day and 1-year survival in patients undergoing surgical treatment for spinal metastasis

Published:January 13, 2022DOI:https://doi.org/10.1016/j.clnu.2022.01.011

      Summary

      Background and aims

      Survival estimation for patients with spinal metastasis is crucial to treatment decisions. Psoas muscle area (PMA), a surrogate for total muscle mass, has been proposed as a useful survival prognosticator. However, few studies have validated the predictive value of decreased PMA in an Asian cohort or its predictive value after controlling for existing preoperative scoring systems (PSSs). In this study, we aim to answer: (1) Is PMA associated with survival in Han Chinese patients with spinal metastasis? (2) Is PMA a good prognosticator according to concordance index (c-index) and decision curve analysis (DCA) after controlling for six existing and commonly used PSSs?

      Methods

      This study included 180 adult (≥18 years old) Taiwanese patients with a mean age of 58.3 years (range: 22–85) undergoing surgical treatment for spinal metastasis. A patient's PMA was classified into decreased, medium, and large if it fell into the lower (0–33%), middle (33–67%), and upper (67–100%) 1/3 in the study cohort, respectively. We used logistic and cox proportional-hazard regressions to assess whether PMA was associated with 90-day, 1-year, and overall survival. The model performance before and after addition of PMA to six commonly used PSSs, including Tomita score, original Tokuhashi score, revised Tokuhashi score, modified Bauer score, New England Spinal Metastasis Score, and Skeletal Oncology Research Group machine learning algorithms (SORG-MLAs), was compared by c-index and DCA to determine if PMA was a useful survival prognosticator.

      Results

      Patients with a larger PMA is associated with better 90-day, but not 1-year, survival. The model performance of 90-day survival prediction improved after PMA was incorporated into all PSSs except SORG-MLAs. PMA barely improved the discriminatory ability (c-index, 0.74; 95% confidence interval [CI], 0.67–0.82 vs. c-index, 0.74; 95% CI, 0.66–0.81) and provided little gain of clinical net benefit on DCA for SORG-MLAs’ 90-day survival prediction.

      Conclusions

      PMA is a prognosticator for 90-day survival and improves the discriminatory ability of earlier-proposed PSSs in our Asian cohort. However, incorporating PMA into more modern PSSs such as SORG-MLAs did not significantly improve its prediction performance.

      Keywords

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      References

        • Walker M.P.
        • Yaszemski M.J.
        • Kim C.W.
        • Talac R.
        • Currier B.L.
        Metastatic disease of the spine: evaluation and treatment.
        Clin Orthop Relat Res. 2003; : S165-S175
        • Lau D.
        • Chan A.K.
        • Theologis A.A.
        • Chou D.
        • Mummaneni P.V.
        • Burch S.
        • et al.
        Costs and readmission rates for the resection of primary and metastatic spinal tumors: a comparative analysis of 181 patients.
        J Neurosurg Spine. 2016; 25: 366-378
        • Massaad E.
        • Shin J.H.
        Commentary: sarcopenia as a prognostic factor for 90-day and overall mortality in patients undergoing spine surgery for metastatic tumors: a multi-center retrospective cohort study.
        Neurosurgery. 2020; 87: E550-E551
        • Benton J.A.
        • De la Garza Ramos R.
        • Yassari R.
        Commentary: sarcopenia as a prognostic factor for 90-day and overall mortality in patients undergoing spine surgery for metastatic tumors: a multi-center retrospective cohort study.
        Neurosurgery. 2020; 87: E547-E549
        • Malik A.T.
        • Alexander J.H.
        • Mayerson J.L.
        • Khan S.N.
        • Scharschmidt T.J.
        Is surgical resection of the primary site associated with an improved overall survival for patients with primary malignant bone tumors who have metastatic disease at presentation?.
        Clin Orthop Relat Res. 2020; 478: 2284-2295
        • Tokuhashi Y.
        • Kawano H.
        • Ohsaka S.
        • Matsuzaki H.
        • Toriyama S.
        [A scoring system for preoperative evaluation of the prognosis of metastatic spine tumor (a preliminary report)].
        Nihon Seikeigeka Gakkai Zasshi. 1989; 63: 482-489
        • Tokuhashi Y.
        • Matsuzaki H.
        • Toriyama S.
        • Kawano H.
        • Ohsaka S.
        Scoring system for the preoperative evaluation of metastatic spine tumor prognosis.
        Spine. 1990; 15: 1110-1113
        • Tomita K.
        • Kawahara N.
        • Kobayashi T.
        • Yoshida A.
        • Murakami H.
        • Akamaru T.
        Surgical strategy for spinal metastases.
        Spine. 2001; 26: 298-306
        • Tokuhashi Y.
        • Matsuzaki H.
        • Oda H.
        • Oshima M.
        • Ryu J.
        A revised scoring system for preoperative evaluation of metastatic spine tumor prognosis.
        Spine. 2005; 30: 2186-2191
        • Leithner A.
        • Radl R.
        • Gruber G.
        • Hochegger M.
        • Leithner K.
        • Welkerling H.
        • et al.
        Predictive value of seven preoperative prognostic scoring systems for spinal metastases.
        Eur Spine J. 2008; 17: 1488-1495
        • Ghori A.K.
        • Leonard D.A.
        • Schoenfeld A.J.
        • Saadat E.
        • Scott N.
        • Ferrone M.L.
        • et al.
        Modeling 1-year survival after surgery on the metastatic spine.
        Spine J. 2015; 15: 2345-2350
        • Karhade A.V.
        • Thio Q.
        • Ogink P.T.
        • Bono C.M.
        • Ferrone M.L.
        • Oh K.S.
        • et al.
        Predicting 90-day and 1-year mortality in spinal metastatic disease: development and internal validation.
        Neurosurgery. 2019; 85: E671-E681
        • Ahmed A.K.
        • Goodwin C.R.
        • Heravi A.
        • Kim R.
        • Abu-Bonsrah N.
        • Sankey E.
        • et al.
        Predicting survival for metastatic spine disease: a comparison of nine scoring systems.
        Spine J. 2018; 18: 1804-1814
        • Schoenfeld A.J.
        • Le H.V.
        • Marjoua Y.
        • Leonard D.A.
        • Belmont Jr., P.J.
        • Bono C.M.
        • et al.
        Assessing the utility of a clinical prediction score regarding 30-day morbidity and mortality following metastatic spinal surgery: the New England Spinal Metastasis Score (NESMS).
        Spine J. 2016; 16: 482-490
        • Tabouret E.
        • Cauvin C.
        • Fuentes S.
        • Esterni B.
        • Adetchessi T.
        • Salem N.
        • et al.
        Reassessment of scoring systems and prognostic factors for metastatic spinal cord compression.
        Spine J. 2015; 15: 944-950
        • Bongers M.E.R.
        • Karhade A.V.
        • Villavieja J.
        • Groot O.Q.
        • Bilsky M.H.
        • Laufer I.
        • et al.
        Does the SORG algorithm generalize to a contemporary cohort of patients with spinal metastases on external validation?.
        Spine J. 2020; 20: 1646-1652
        • Karhade A.V.
        • Ahmed A.K.
        • Pennington Z.
        • Chara A.
        • Schilling A.
        • Thio Q.
        • et al.
        External validation of the SORG 90-day and 1-year machine learning algorithms for survival in spinal metastatic disease.
        Spine J. 2020; 20: 14-21
        • Yang J.J.
        • Chen C.W.
        • Fourman M.S.
        • Bongers M.E.R.
        • Karhade A.V.
        • Groot O.Q.
        • et al.
        International external validation of the SORG machine learning algorithms for predicting 90-day and 1-year survival of patients with spine metastases using a Taiwanese cohort.
        Spine J. 2021;
        • Shah A.A.
        • Karhade A.V.
        • Park H.Y.
        • Sheppard W.L.
        • Macyszyn L.J.
        • Everson R.G.
        • et al.
        Updated external validation of the SORG machine learning algorithms for prediction of ninety-day and one-year mortality after surgery for spinal metastasis.
        Spine J. 2021;
        • Dodds R.
        • Sayer A.A.
        Sarcopenia and frailty: new challenges for clinical practice.
        Clin Med. 2015; 15: s88-s91
        • Baracos V.E.
        Psoas as a sentinel muscle for sarcopenia: a flawed premise.
        J Cachexia Sarcopenia Muscle. 2017; 8: 527-528
        • Bourassa-Moreau E.
        • Versteeg A.
        • Moskven E.
        • Charest-Morin R.
        • Flexman A.
        • Ailon T.
        • et al.
        Sarcopenia, but not frailty, predicts early mortality and adverse events after emergent surgery for metastatic disease of the spine.
        Spine J. 2020; 20: 22-31
        • Fujiwara N.
        • Nakagawa H.
        • Kudo Y.
        • Tateishi R.
        • Taguri M.
        • Watadani T.
        • et al.
        Sarcopenia, intramuscular fat deposition, and visceral adiposity independently predict the outcomes of hepatocellular carcinoma.
        J Hepatol. 2015; 63: 131-140
        • Hasselager R.
        • Gogenur I.
        Core muscle size assessed by perioperative abdominal CT scan is related to mortality, postoperative complications, and hospitalization after major abdominal surgery: a systematic review.
        Langenbeck's Arch Surg. 2014; 399: 287-295
        • Itoh S.
        • Shirabe K.
        • Matsumoto Y.
        • Yoshiya S.
        • Muto J.
        • Harimoto N.
        • et al.
        Effect of body composition on outcomes after hepatic resection for hepatocellular carcinoma.
        Ann Surg Oncol. 2014; 21: 3063-3068
        • Miller J.
        • Wells L.
        • Nwulu U.
        • Currow D.
        • Johnson M.J.
        • Skipworth R.J.E.
        Validated screening tools for the assessment of cachexia, sarcopenia, and malnutrition: a systematic review.
        Am J Clin Nutr. 2018; 108: 1196-1208
        • Takenaka Y.
        • Oya R.
        • Takemoto N.
        • Inohara H.
        Predictive impact of sarcopenia in solid cancers treated with immune checkpoint inhibitors: a meta-analysis.
        J Cachexia Sarcopenia Muscle. 2021;
        • Weerink L.B.M.
        • van der Hoorn A.
        • van Leeuwen B.L.
        • de Bock G.H.
        Low skeletal muscle mass and postoperative morbidity in surgical oncology: a systematic review and meta-analysis.
        J Cachexia Sarcopenia Muscle. 2020; 11: 636-649
        • Hansen L.
        • de Zee M.
        • Rasmussen J.
        • Andersen T.B.
        • Wong C.
        • Simonsen E.B.
        Anatomy and biomechanics of the back muscles in the lumbar spine with reference to biomechanical modeling.
        Spine. 2006; 31: 1888-1899
        • Mourtzakis M.
        • Prado C.M.
        • Lieffers J.R.
        • Reiman T.
        • McCargar L.J.
        • Baracos V.E.
        A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care.
        Appl Physiol Nutr Metabol. 2008; 33: 997-1006
        • Moskven E.
        • Bourassa-Moreau E.
        • Charest-Morin R.
        • Flexman A.
        • Street J.
        The impact of frailty and sarcopenia on postoperative outcomes in adult spine surgery. A systematic review of the literature.
        Spine J. 2018; 18: 2354-2369
        • Wu C.H.
        • Chang M.C.
        • Lyadov V.K.
        • Liang P.C.
        • Chen C.M.
        • Shih T.T.
        • et al.
        Comparing Western and Eastern criteria for sarcopenia and their association with survival in patients with pancreatic cancer.
        Clin Nutr. 2019; 38: 862-869
        • Wu C.H.
        • Liang P.C.
        • Hsu C.H.
        • Chang F.T.
        • Shao Y.Y.
        • Ting-Fang Shih T.
        Total skeletal, psoas and rectus abdominis muscle mass as prognostic factors for patients with advanced hepatocellular carcinoma.
        J Formos Med Assoc. 2021; 120: 559-566
        • Zakaria H.M.
        • Basheer A.
        • Boyce-Fappiano D.
        • Elibe E.
        • Schultz L.
        • Lee I.
        • et al.
        Application of morphometric analysis to patients with lung cancer metastasis to the spine: a clinical study.
        Neurosurg Focus. 2016; 41: E12
        • Zakaria H.M.
        • Massie L.
        • Basheer A.
        • Boyce-Fappiano D.
        • Elibe E.
        • Schultz L.
        • et al.
        Application of morphometrics as a predictor for survival in female patients with breast cancer spinal metastasis: a retrospective cohort study.
        Spine J. 2018; 18: 1798-1803
        • Zakaria H.M.
        • Elibe E.
        • Macki M.
        • Smith R.
        • Boyce-Fappiano D.
        • Lee I.
        • et al.
        Morphometrics predicts overall survival in patients with multiple myeloma spine metastasis: a retrospective cohort study.
        Surg Neurol Int. 2018; 9: 172
        • Zakaria H.M.
        • Llaniguez J.T.
        • Telemi E.
        • Chuang M.
        • Abouelleil M.
        • Wilkinson B.
        • et al.
        Sarcopenia predicts overall survival in patients with lung, breast, prostate, or myeloma spine metastases undergoing stereotactic body radiation therapy (SBRT), independent of histology.
        Neurosurgery. 2020; 86: 705-716
        • Zakaria H.M.
        • Wilkinson B.M.
        • Pennington Z.
        • Saadeh Y.S.
        • Lau D.
        • Chandra A.
        • et al.
        Sarcopenia as a prognostic factor for 90-day and overall mortality in patients undergoing spine surgery for metastatic tumors: a multicenter retrospective cohort study.
        Neurosurgery. 2020; 87: 1025-1036
        • Cuschieri S.
        The STROBE guidelines.
        Saudi J Anaesth. 2019; 13: S31-S34
        • Swanson S.
        • Patterson R.B.
        The correlation between the psoas muscle/vertebral body ratio and the severity of peripheral artery disease.
        Ann Vasc Surg. 2015; 29: 520-525
        • Katagiri H.
        • Okada R.
        • Takagi T.
        • Takahashi M.
        • Murata H.
        • Harada H.
        • et al.
        New prognostic factors and scoring system for patients with skeletal metastasis.
        Cancer Med. 2014; 3: 1359-1367
        • Fryar C.D.
        • Kruszon-Moran D.
        • Gu Q.
        • Ogden C.L.
        Mean body weight, height, waist circumference, and body mass index among adults: United States, 1999-2000 through 2015-2016.
        Natl Health Stat Report, 2018: 1-16
        • Hsieh T.H.
        • Lee J.J.
        • Yu E.W.
        • Hu H.Y.
        • Lin S.Y.
        • Ho C.Y.
        Association between obesity and education level among the elderly in Taipei, Taiwan between 2013 and 2015: a cross-sectional study.
        Sci Rep. 2020; 10: 20285
        • Hamaguchi Y.
        • Kaido T.
        • Okumura S.
        • Kobayashi A.
        • Shirai H.
        • Yao S.
        • et al.
        Proposal for new selection criteria considering pre-transplant muscularity and visceral adiposity in living donor liver transplantation.
        J Cachexia Sarcopenia Muscle. 2018; 9: 246-254
        • Prado C.M.
        • Lieffers J.R.
        • McCargar L.J.
        • Reiman T.
        • Sawyer M.B.
        • Martin L.
        • et al.
        Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study.
        Lancet Oncol. 2008; 9: 629-635
        • Cortet B.
        • Cotten A.
        • Boutry N.
        • Dewatre F.
        • Flipo R.M.
        • Duquesnoy B.
        • et al.
        Percutaneous vertebroplasty in patients with osteolytic metastases or multiple myeloma.
        Rev Rhum Engl Ed. 1997; 64: 177-183
        • Barlev A.
        • Song X.
        • Ivanov B.
        • Setty V.
        • Chung K.
        Payer costs for inpatient treatment of pathologic fracture, surgery to bone, and spinal cord compression among patients with multiple myeloma or bone metastasis secondary to prostate or breast cancer.
        J Manag Care Pharm. 2010; 16: 693-702
        • Pielkenrood B.J.
        • van Urk P.R.
        • van der Velden J.M.
        • Kasperts N.
        • Verhoeff J.J.C.
        • Bol G.H.
        • et al.
        Impact of body fat distribution and sarcopenia on the overall survival in patients with spinal metastases receiving radiotherapy treatment: a prospective cohort study.
        Acta Oncol. 2020; 59: 291-297
        • Karhade A.V.
        • Thio Q.
        • Ogink P.T.
        • Shah A.A.
        • Bono C.M.
        • Oh K.S.
        • et al.
        Development of machine learning algorithms for prediction of 30-day mortality after surgery for spinal metastasis.
        Neurosurgery. 2019; 85: E83-E91
        • Thio Q.
        • Karhade A.V.
        • Bindels B.J.J.
        • Ogink P.T.
        • Bramer J.A.M.
        • Ferrone M.L.
        • et al.
        Development and internal validation of machine learning algorithms for preoperative survival prediction of extremity metastatic disease.
        Clin Orthop Relat Res. 2020; 478: 322-333
        • Christodoulou E.
        • Ma J.
        • Collins G.S.
        • Steyerberg E.W.
        • Verbakel J.Y.
        • Van Calster B.
        A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models.
        J Clin Epidemiol. 2019; 110: 12-22
        • Kuhle S.
        • Maguire B.
        • Zhang H.
        • Hamilton D.
        • Allen A.C.
        • Joseph K.S.
        • et al.
        Comparison of logistic regression with machine learning methods for the prediction of fetal growth abnormalities: a retrospective cohort study.
        BMC Pregnancy Childbirth. 2018; 18: 333
        • Pua Y.H.
        • Kang H.
        • Thumboo J.
        • Clark R.A.
        • Chew E.S.
        • Poon C.L.
        • et al.
        Machine learning methods are comparable to logistic regression techniques in predicting severe walking limitation following total knee arthroplasty.
        Knee Surg Sports Traumatol Arthrosc. 2020; 28: 3207-3216
        • Nusinovici S.
        • Tham Y.C.
        • Chak Yan M.Y.
        • Wei Ting D.S.
        • Li J.
        • Sabanayagam C.
        • et al.
        Logistic regression was as good as machine learning for predicting major chronic diseases.
        J Clin Epidemiol. 2020; 122: 56-69