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CompletedNCT03141957HELPUpdated May 8, 2017

Hypermetabolism in the Elderly Lung Cancer Patient

An observational study in Non-small Cell Lung Carcinoma, sponsored by University of Paris 5 - Rene Descartes. Completed at 1 site in France. Open to participants aged 18 Years to 95 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2017-05-08.

Sponsored by University of Paris 5 - Rene Descartes · Observational

Study type
Observational
Model
Case-control
Time perspective
Cross-sectional
Enrollment
27
Ages
18 Years to 95 Years
Sex
All
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Study summary

Aging and cancer are two conditions associated with extensive metabolic changes that can cause malnutrition. However, the clinical features and the underlying mechanisms leading to malnutrition are different in these two cases. We therefore wonder how age can influence the metabolic response to cancer.

Read the detailed description

During aging, among other physiological modifications, inactivity and insulin resistance cause a progressive muscle loss associated with a decrease in resting energy expenditure (REE). In cancer, loud inflammation background also provokes a decrease in muscle mass as well as in fat mass. However, previous studies reported an increased REE, termed hypermetabolism, probably linked to inflammation.

Data concerning response to aggression in the elderly patient is scarce and even inexistent when it comes to cancer. The investigators hypothesize that the mitochondrial dysfunction that comes with aging and that decreases the ATP rendering per unit of energy-producing nutrient oxidized increases the amount of nutrient to be consumed in order to sustain to energy needs. Therefore, in this situation, elderly patients could have a higher rate or degree of hypermetabolism than younger patients.

The primary objective of this study is to assess the effect of aging on the metabolic response to cancer assessed by resting energy expenditure measured by indirect calorimetry corrected by whole body fat free mass calculated from single slice CT imaging at the third lumbar vertebra.

The secondary objective of this study is to point out some inflammatory or endocrine determinants of these energy metabolism changes in the cancer patient.

Non-small cell lung carcinoma seems to be a relevant choice for this study because it is frequently associated with cachexia and the literature reports a high rate of hypermetabolism in this cancer.

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Conditions studied

  • Non-small Cell Lung Carcinoma

Keywords

  • Aging
  • Hypermetabolism
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In context

Carcinoma, Non-Small-Cell Lung

6,485 studies on the registry are indexed under Carcinoma, Non-Small-Cell Lung; 1,630 are open to participants now.

This study's enrollment of 27 is below the median of 161 across 948 observational studies indexed under Carcinoma, Non-Small-Cell Lung.

Browse Carcinoma, Non-Small-Cell Lung studies →

Lead sponsor

University of Paris 5 - Rene Descartes is the lead sponsor of 17 studies on the registry; none are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
18 Years to 95 Years
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Non-probability sample

Study population

The population is selected from the patients coming for their one-day pre-treatment evaluation at the oncology ward of the Cochin Hospital.

Inclusion criteria

  • Non-small cell lung carcinoma

Exclusion criteria

Exclusion Criteria:

  • Imbalanced Diabetes
  • Imbalanced dysthyroidia
  • Surgery within two month prior inclusion
  • Any chronic auto-immune or inflammatory disease
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Study design

Observational model
Case-control
Time perspective
Cross-sectional
Enrollment
27 participants (actual)
Patient registry
No

Groups and cohorts

  • Young patients

    Patients with non-small cell lung carcinoma younger than 75y

  • Elderly patients

    Patients with non-small cell lung carcinoma aged 75 or more

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What researchers measure

Primary outcomes

  1. Measured resting energy expenditure (mREE) in kilocalorie per day

    Energy expenditure is measured by indirect calorimetry.

    Time frame: Day 0

Secondary outcomes

  1. Blood C-Reactive Protein in milligram per milliliter

    Inflammatory status

    Time frame: Day 0

  2. Blood Interleukine-6 in picogram per milliliter

    Inflammatory status

    Time frame: Day 0

  3. Blood Tumor Necrosis Factor alpha in picogram per milliliter

    Inflammatory status

    Time frame: Day 0

  4. Blood Insulin in milliunit per liter

    Endocrine Status - Glucose Homeostasis

    Time frame: Day 0

  5. Blood ultra-sensitive Thyroid Stimulating Hormone in milliunit per liter

    Endocrine Status - Thyroid Function

    Time frame: Day 0

  6. Blood Insulin-like Growth Factor 1 in nanogram per liter

    Endocrine Status - Somatotropic axis

    Time frame: Day 0

  7. Blood Glucose in millimole per liter

    Endocrine Status

    Time frame: Day 0

  8. Homeostasis Model assessment of Insulin resistance

    Aggregates blood Insulin and glucose level as an insulin resistance score

    Time frame: Day 0

  9. Lean Body Mass in kilogram

    Estimated from muscular area at the third lombular vertebra from CT-scan

    Time frame: Day 0

  10. energy intake in kilocalorie per day

    Estimated by a qualified dietetican

    Time frame: Day 0

  11. Albumin in gram per liter

    Nutritional Satus

    Time frame: Day 0

  12. Transthyretin in gram per liter

    Nutritional Satus

    Time frame: Day 0

  13. Predicted resting energy expenditure (HB) in kilocalorie per day

    REE estimated with Harris \& Benedict Formula

    Time frame: Day 0

  14. Percentage of estimated energy expenditure

    Percentage of HB : (mREE/HB) x 100

    Time frame: Day 0

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Study locations

1 site
  • Hopital Cochin
    Paris, 75014, France
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References and documents

Publications

  • Ulmann G, Jouinot A, Tlemsani C, Curis E, Kousignian I, Neveux N, Durand JP, Goldwasser F, Cynober L, De Bandt JP. Lean Body Mass and Endocrine Status But Not Age Are Determinants of Resting Energy Expenditure in Patients with Non-Small Cell Lung Cancer. Ann Nutr Metab. 2019;75(4):223-230. doi: 10.1159/000504874. Epub 2019 Dec 19. PubMed 31865308 ↗

Individual participant data

Plan to share: No

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on May 8, 2017, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT03141957
Lead sponsor
University of Paris 5 - Rene Descartes
Responsible party
Guillaume Ulmann (Doctor, University of Paris 5 - Rene Descartes) — Principal investigator
First posted
May 5, 2017
Start date
Jan 2016
Primary completion
Nov 2016
Completion
Nov 2016
Last update
May 8, 2017

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in May 2017. You cannot join it, but the record below documents what was studied.

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