Skeletal muscle changes after elective colorectal cancer resection: a longitudinal study
File(s)
Author(s)
Type
Journal Article
Abstract
Background
Muscle depletion is a poor prognostic indicator in colorectal cancer (CRC) patients, but there were no data assessing comparative temporal body composition changes following elective CRC surgery. We examined patient skeletal muscle index trajectories over time after surgery and determined factors that may contribute to those alterations.
Methods
Patients diagnosed with CRC undergoing elective surgical resection between 2006 and 2013 were included in this study. Image analysis of serial computed tomography (CT) scans was used to calculate lumbar skeletal muscle index (LSMI). A multilevel mixed-effect linear regression model was applied using STATA (version 12.0) using the xtmixed command to fit growth curve models (GCM) for LSMI and time.
Results
In 856 patients, a total of 2136 CT images were analyzed; 856 (38.2 %) were preoperative. A quadratic GCM with random intercept and random slope for patients’ LSMI was identified that demonstrated laparoscopy produces a positive change on the LSMI curve [estimate = 0.17 cm2/m2, standard error (SE) 0.06 cm2/m2; p = 0.03], whereas Union for International Cancer Control (UICC) stage III + IV disease contributed to a negative curve change (estimate = −0.19 cm2/m2, SE 0.09 cm2/m2; p = 0.03). Older age (p < 0.01), female gender (p < 0.01), higher American Society of Anesthesiologists (ASA) score (p < 0.01), and altered systemic inflammatory response [SIR] (p = 0.03) were factors significantly associated with lower values of LSMI over time.
Conclusion
In patients undergoing CRC surgery, laparoscopy and the absence of a significantly elevated SIR favored preservation and restoration of skeletal muscle, postoperatively. These emerging data may permit the development of new treatment protocols whereby monitoring and modification of body composition has therapeutic potential.
It is becoming increasingly clear that a variety of body composition changes occur in cancer patients, and that muscle depletion is a common, albeit in most, occult feature. Muscle depletion is characterized by reduction in muscle size (myopenia) and an increased infiltration by inter- and intramuscular fat, described as myosteatosis.1,2 The incidence of muscle depletion varies from 15 to 70 % for patients treated for CRC,3 and evidence also demonstrates that muscle depletion is associated with poorer outcomes in patients treated for cancer.4,5 For CRC patients treated surgically, myopenia negatively impacts short-term outcomes, including mortality, morbidity, and functional recovery.3 Muscle depletion, estimated from CTBC analysis, has also been found to be a prognostic factor for developing severe toxicity in CRC patients receiving chemotherapy.6 Finally, emerging data suggest that myopenia can be an independent predictor of poorer survival after CRC treatment; however, neither the point of onset of muscle depletion nor the patterns of muscle alterations over time and their precipitants are known. Therefore, there is a need to identify whether body composition changes assessable by surveillance imaging after CRC can be related to specific clinicopathological or treatment factors that, once identified, might allow muscle depletion to be contained or modified.
Growth curve modeling (GCM) is an advanced method for demonstrating within-patient and between-patient variation in outcomes measured across different time points over a follow-up period.7 The GCM approach has allowed researchers to overcome problems in studies that assess comparisons of the intraindividual changes over time. More traditional methods examining changes of time, such as analysis of variance and analysis of covariance, are problematic and are limited, mandating accuracy in equal group sizes, a condition that is very difficult to meet.8,9
Using the GCM approach, we aimed to not only examine how patient body composition, as determined by skeletal muscle index trajectories, varied over time after elective surgery for CRC but also to determine specific factors that may contribute to alterations over time.
Muscle depletion is a poor prognostic indicator in colorectal cancer (CRC) patients, but there were no data assessing comparative temporal body composition changes following elective CRC surgery. We examined patient skeletal muscle index trajectories over time after surgery and determined factors that may contribute to those alterations.
Methods
Patients diagnosed with CRC undergoing elective surgical resection between 2006 and 2013 were included in this study. Image analysis of serial computed tomography (CT) scans was used to calculate lumbar skeletal muscle index (LSMI). A multilevel mixed-effect linear regression model was applied using STATA (version 12.0) using the xtmixed command to fit growth curve models (GCM) for LSMI and time.
Results
In 856 patients, a total of 2136 CT images were analyzed; 856 (38.2 %) were preoperative. A quadratic GCM with random intercept and random slope for patients’ LSMI was identified that demonstrated laparoscopy produces a positive change on the LSMI curve [estimate = 0.17 cm2/m2, standard error (SE) 0.06 cm2/m2; p = 0.03], whereas Union for International Cancer Control (UICC) stage III + IV disease contributed to a negative curve change (estimate = −0.19 cm2/m2, SE 0.09 cm2/m2; p = 0.03). Older age (p < 0.01), female gender (p < 0.01), higher American Society of Anesthesiologists (ASA) score (p < 0.01), and altered systemic inflammatory response [SIR] (p = 0.03) were factors significantly associated with lower values of LSMI over time.
Conclusion
In patients undergoing CRC surgery, laparoscopy and the absence of a significantly elevated SIR favored preservation and restoration of skeletal muscle, postoperatively. These emerging data may permit the development of new treatment protocols whereby monitoring and modification of body composition has therapeutic potential.
It is becoming increasingly clear that a variety of body composition changes occur in cancer patients, and that muscle depletion is a common, albeit in most, occult feature. Muscle depletion is characterized by reduction in muscle size (myopenia) and an increased infiltration by inter- and intramuscular fat, described as myosteatosis.1,2 The incidence of muscle depletion varies from 15 to 70 % for patients treated for CRC,3 and evidence also demonstrates that muscle depletion is associated with poorer outcomes in patients treated for cancer.4,5 For CRC patients treated surgically, myopenia negatively impacts short-term outcomes, including mortality, morbidity, and functional recovery.3 Muscle depletion, estimated from CTBC analysis, has also been found to be a prognostic factor for developing severe toxicity in CRC patients receiving chemotherapy.6 Finally, emerging data suggest that myopenia can be an independent predictor of poorer survival after CRC treatment; however, neither the point of onset of muscle depletion nor the patterns of muscle alterations over time and their precipitants are known. Therefore, there is a need to identify whether body composition changes assessable by surveillance imaging after CRC can be related to specific clinicopathological or treatment factors that, once identified, might allow muscle depletion to be contained or modified.
Growth curve modeling (GCM) is an advanced method for demonstrating within-patient and between-patient variation in outcomes measured across different time points over a follow-up period.7 The GCM approach has allowed researchers to overcome problems in studies that assess comparisons of the intraindividual changes over time. More traditional methods examining changes of time, such as analysis of variance and analysis of covariance, are problematic and are limited, mandating accuracy in equal group sizes, a condition that is very difficult to meet.8,9
Using the GCM approach, we aimed to not only examine how patient body composition, as determined by skeletal muscle index trajectories, varied over time after elective surgery for CRC but also to determine specific factors that may contribute to alterations over time.
Date Issued
2016-03-22
Date Acceptance
2016-03-22
Citation
Annals of Surgical Oncology, 2016, 23 (8), pp.2539-2547
ISSN
1534-4681
Publisher
Springer Verlag
Start Page
2539
End Page
2547
Journal / Book Title
Annals of Surgical Oncology
Volume
23
Issue
8
Copyright Statement
© The Author(s) 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
License URL
Identifier
PII: 10.1245/s10434-016-5188-1
Subjects
Oncology & Carcinogenesis
1112 Oncology And Carcinogenesis
Publication Status
Published