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@PHDTHESIS{Marquardt:986583,
      author       = {Marquardt, Jan Peter},
      othercontributors = {Kuhl, Christiane and Brümmendorf, Tim Henrik},
      title        = {{P}ercentile-based averaging and skeletal muscle gauge
                      improve body composition analysis: validation at multiple
                      vertebral levels},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2024-05284},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2023},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University 2024; Dissertation, Rheinisch-Westfälische
                      Technische Hochschule Aachen, 2023},
      abstract     = {Background: Skeletal muscle metrics on computed tomography
                      (CT) correlate with clinical and patient-reported outcomes.
                      We hypothesize that aggregating skeletal muscle measurements
                      from multiple vertebral levels and skeletal muscle gauge
                      (SMG) better predict outcomes than skeletal muscle
                      radioattenuation (SMRA) or -index (SMI) at a single
                      vertebral level. Methods: We performed a secondary analysis
                      of prospectively collected clinical (overall survival,
                      hospital readmission, time to unplanned hospital readmission
                      or death, and readmission or death within 90 days) and
                      patient-reported outcomes (physical and psychological
                      symptom burden captured as Edmonton Symptom Assessment Scale
                      and Patient Health Questionnaire) of patients with advanced
                      cancer who experienced an unplanned admission to
                      Massachusetts General Hospital from 2014 to 2016. First, we
                      assessed the correlation of skeletal muscle cross-sectional
                      area, SMRA, SMI, and SMG at one or more of the following
                      thoracic (T) or lumbar (L) vertebral levels: T5, T8, T10,
                      and L3 on CT scans obtained ≤50 days before index
                      assessment. Second, we aggregated measurements across all
                      available vertebral levels using percentile-based averaging
                      (PBA) to create the average percentile. Third, we
                      constructed one regression model adjusted for age, sex,
                      sociodemographic factors, cancer type, body mass index, and
                      intravenous contrast for each combination of (i) vertebral
                      level and average percentile, (ii) muscle metrics (SMRA,
                      SMI, $\&$ SMG), and (iii) clinical and patient-reported
                      outcomes. Fourth, we compared the performance of vertebral
                      levels and muscle metrics by ranking otherwise identical
                      models by concordance statistic, number of included
                      patients, coefficient of determination, and significance of
                      muscle metric. Results: We included 846 patients (mean age:
                      63.5 ± 12.9 years, $50.5\%$ males) with advanced cancer
                      [predominantly gastrointestinal $(32.9\%)$ or lung
                      $(18.9\%)].$ The correlation of muscle measurements between
                      vertebral levels ranged from 0.71 to 0.84 for SMRA and 0.67
                      to 0.81 for SMI. The correlation of individual levels with
                      the average percentile was 0.90–0.93 for SMRA and
                      0.86–0.92 for SMI. The intrapatient correlation of SMRA
                      with SMI was 0.21–0.40. PBA allowed for inclusion of
                      $8–47\%$ more patients than any single-level analysis. PBA
                      outperformed single-level analyses across all comparisons
                      with average ranks 2.6, 2.9, and 1.6 for concordance
                      statistic, coefficient of determination, and significance
                      (range 1–5, μ = 3), respectively. On average, SMG
                      outperformed SMRA and SMI across outcomes and vertebral
                      levels: the average rank of SMG was 1.4, 1.4, and 1.4 for
                      concordance statistic, coefficient of determination, and
                      significance (range 1–3, μ = 2), respectively.
                      Conclusions: Multivertebral level skeletal muscle analyses
                      using PBA and SMG independently and additively outperform
                      analyses using individual levels and SMRA or SMI.},
      cin          = {532010-2 ; 936210},
      ddc          = {610},
      cid          = {$I:(DE-82)532010-2_20140620$},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2024-05284},
      url          = {https://publications.rwth-aachen.de/record/986583},
}