Letter to the Editor: Integrating Skeletal Muscle Mass and Radiodensity Improves Outcome Prediction and Correlation in Oncologic Studies

View More View Less
  • 1 University of Alabama at Birmingham, Birmingham, AL, Email: gwillia@uab.edu
  • | 2 The University of North Carolina, Chapel Hill, NC
  • | 3 The University of North Carolina, Chapel Hill, NC, and Rambam Health Care Campus, Haifa, Israel

Re: Camila Santos Rodrigues, Gabriela Villaça Chaves. Skeletal Muscle Quality Beyond Average Muscle Attenuation: A Proposal of Skeletal Muscle Phenotypes to Predict Short-Term Survival in Patients With Endometrial Cancer. J Natl Compr Canc Netw 2018;16(2):153–160.

We read with great interest the recent article by Rodrigues and Chaves1 regarding the association of skeletal muscle (SM) phenotypes with short-term survival in patients with endometrial cancer. Understanding the impact of both muscle mass and radiodensity is critically important, and we appreciate the authors' innovative strategy to incorporate both these variables. Given the growing literature on the importance of muscle content and underlying myosteatosis, CT-based body composition assessments should include an assessment of not only SM mass but also muscle radiodensity, a surrogate measurement of muscle composition.

However, we propose an alternative strategy for integrating these important measurements. Rather than dichotomizing participants as high or low radiodensity, why not integrate these 2 variables into 1 continuous variable? Because both muscle mass and radiodensity are defined independently and both are prognostic of many adverse cancer outcomes, we have proposed a mathematical combination of these measures.2 Multiplying SM index and the mean SM radiodensity (SMD) from cross-sectional CT imaging at the L3 vertebrae allows for the creation of a new variable, which we have termed “skeletal muscle gauge” (SMG), which retains equal influence of both variables. This method allows for exploring these 2 important muscle components as a single continuous variable with equal weighting rather than creating arbitrary cut points for each. SMG is more highly correlated with aging than either muscle mass or radiodensity alone.2

In other recent studies, SMG was shown to be the best predictor of grade 3/4 chemotherapy toxicity in women with early-stage breast cancer undergoing anthracycline and taxane-based chemotherapy.3 Other investigators using a similar integrated method for the psoas muscle alone found total psoas gauge was a better predictor of surgical outcomes in patients undergoing radical gastrectomy for gastric cancer.4 Although the use of subranges for radiodensity measurements provide ease of presentation and simplifies statistical analysis, maintaining continuous dimensions for radiodensity allow for increased statistical power to detect a relationship between radiodensity and patient outcomes.5

Further research is needed to explore the relationship and interplay of both SM mass and radiodensity with adverse outcomes in oncology. With the goal of improved outcome predictions, diagnoses, and treatments, we suggest that future studies evaluate and integrate SMD in a linear rather than dichotomous manner with SM mass.

Call for Correspondence

JNCCN is committed to providing a forum to enhance collaboration between academic medicine and the community physician. We welcome comments about the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines), articles published in the journal, or any other topic relating to cancer prevention, detection, treatment, supportive care, or survivorship.

Please send correspondence to JNCCN.edmgr.com or to JNCCN@nccn.org.

Letters should be no more than 400 words, with no more than 5 references if included. Please include the full names, degrees, and affiliations of all letter authors and a phone number or e-mail address for contact.

Letters are considered for publication as space allows. NCCN reserves the right not to publish correspondence for any reason it deems appropriate. All letters are subject to editing and/or abridgment.

References

  • 1.

    Rodrigues CS, Chaves GV. Skeletal muscle quality beyond average muscle attenuation: a proposal of skeletal muscle phenotypes to predict short-term survival in patients with endometrial cancer. J Natl Compr Canc Netw 2018;16:153160.

    • Search Google Scholar
    • Export Citation
  • 2.

    Weinberg MS, Shachar SS, Muss HB et al.. Beyond sarcopenia: characterization and integration of skeletal muscle quantity and radiodensity in a curable breast cancer population. Breast J 2017;24:278284.

    • Search Google Scholar
    • Export Citation
  • 3.

    Shachar SS, Deal AM, Weinberg M et al.. Body composition as a predictor of toxicity in patients receiving anthracycline and taxane-based chemotherapy for early-stage breast cancer. Clin Cancer Res 2017;23:35373543.

    • Search Google Scholar
    • Export Citation
  • 4.

    Lu J, Zheng ZF, Li P et al.. A novel preoperative skeletal muscle measure as a predictor of postoperative complications, long-term survival and tumor recurrence for patients with gastric cancer after radical gastrectomy. Ann Surg Oncol 2018;25:439448.

    • Search Google Scholar
    • Export Citation
  • 5.

    Altman DG, Royston P. The cost of dichotomising continuous variables. BMJ 2006;332:1080.

  • 1.

    Rodrigues CS, Chaves GV. Skeletal muscle quality beyond average muscle attenuation: a proposal of skeletal muscle phenotypes to predict short-term survival in patients with endometrial cancer. J Natl Compr Canc Netw 2018;16:153160.

    • Search Google Scholar
    • Export Citation
  • 2.

    Weinberg MS, Shachar SS, Muss HB et al.. Beyond sarcopenia: characterization and integration of skeletal muscle quantity and radiodensity in a curable breast cancer population. Breast J 2017;24:278284.

    • Search Google Scholar
    • Export Citation
  • 3.

    Shachar SS, Deal AM, Weinberg M et al.. Body composition as a predictor of toxicity in patients receiving anthracycline and taxane-based chemotherapy for early-stage breast cancer. Clin Cancer Res 2017;23:35373543.

    • Search Google Scholar
    • Export Citation
  • 4.

    Lu J, Zheng ZF, Li P et al.. A novel preoperative skeletal muscle measure as a predictor of postoperative complications, long-term survival and tumor recurrence for patients with gastric cancer after radical gastrectomy. Ann Surg Oncol 2018;25:439448.

    • Search Google Scholar
    • Export Citation
  • 5.

    Altman DG, Royston P. The cost of dichotomising continuous variables. BMJ 2006;332:1080.

  • 1.

    Rodrigues CS, Chaves GV. Skeletal muscle quality beyond average muscle attenuation: a proposal of skeletal muscle phenotypes to predict short-term survival in patients with endometrial cancer. J Natl Compr Canc Netw 2018;16:153160.

    • Search Google Scholar
    • Export Citation
  • 2.

    Weinberg MS, Shachar SS, Muss HB et al.. Beyond sarcopenia: characterization and integration of skeletal muscle quantity and radiodensity in a curable breast cancer population. Breast J 2017;24:278284.

    • Search Google Scholar
    • Export Citation
  • 3.

    Aubrey J, Esfandiari N, Baracos VE et al.. Measurement of skeletal muscle radiation attenuation and basis of its biological variation. Acta Physiol (Oxf) 2014;210:489497.

    • Search Google Scholar
    • Export Citation
  • 4.

    de Paula NS, de Aguiar KB, Aredes MA, Chaves GV. Sarcopenia and skeletal muscle quality as predictors of postoperative complication and early mortality in gynecologic cancer. Int J Gynecol Cancer 2018;28:412420.

    • Search Google Scholar
    • Export Citation
  • 5.

    de Paula NS, Rodrigues CS, Chaves GV. Comparison of the prognostic value of different skeletal muscle radiodensity parameters in endometrial cancer [published online April 25, 2018]. Eur J Clin Nutr, doi: 10.1038/s41430-018-0163-5

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 383 34 4
PDF Downloads 134 48 5
EPUB Downloads 0 0 0