| Literature DB >> 30266081 |
Ragnhild Habberstad1,2, Trude Camilla Salvesen Frøseth3, Nina Aass4,5, Tatiana Abramova6, Theo Baas6, Siri Tessem Mørkeset6, Augusto Caraceni7, Barry Laird8, Jason W Boland9, Romina Rossi10, Elena Garcia-Alonso11, Hanne Stensheim5,12, Jon Håvard Loge4,5, Marianne Jensen Hjermstad4, Ellen Bjerkeset4, Asta Bye4, Jo-Åsmund Lund3,6, Tora Skeidsvoll Solheim3,13, Ola Magne Vagnildhaug3,13, Cinzia Brunelli7, Jan Kristian Damås14,15, Tom Eirik Mollnes16,17,18, Stein Kaasa4,5, Pål Klepstad3,19,20.
Abstract
BACKGROUND: Radiation therapy (RT) results in pain relief for about 6 of 10 patients with cancer induced bone pain (CIBP) caused by bone metastases. The high number of non-responders, the long median time from RT to pain response and the risk of adverse effects, makes it important to determine predictors of treatment response. Clinical features such as cancer type, performance status and pain intensity, and biomarkers for osteoclast activity are proposed as predictors of response to RT. However, results are inconsistent and there is a need for better predictors of RT response. A similar argument can be stated for the development of cachexia; there are currently no predictors that can identify patients who will develop cachexia later in the cancer disease trajectory. Experimental and preclinical studies show that pain, depression and cachexia are related to inflammation. However, it is not known if inflammatory biomarkers can predict CIBP, depression or development of cachexia.Entities:
Keywords: Bone metastases; Cachexia; Cancer; Depression; Inflammation; Pain; Palliative; Radiation therapy
Mesh:
Year: 2018 PMID: 30266081 PMCID: PMC6162927 DOI: 10.1186/s12904-018-0362-9
Source DB: PubMed Journal: BMC Palliat Care ISSN: 1472-684X Impact factor: 3.234
Fig. 1Study objectives with Research Questions (RQ)
Flow chart for registrations
| Time of assessment | ||||||
|---|---|---|---|---|---|---|
| Inclusion | 3 W | 8 W | 16 W | 24 W | 1 YR | |
| Screening for inclusion | X | |||||
| Demographics, cancer history, planned RT, previous pain therapy | X | |||||
| New cancer related incidents | X | X | X | X | X | |
| Current use of medications | X | X | X | X | X | X |
| Weight | X | X | X | X | X | X |
| Performance status | X | X | X | X | X | X |
| CT scans for body composition (if available) | X | X | X | X | X | X |
| PG-SGA | X | X | X | X | X | X |
| Pain registrations | X | X | X | X | X | X |
| QLQ-C15 PAL | X | X | X | X | X | X |
| LANSS | X | X | X | |||
| Episodic pain questions | X | X | X | |||
| PHQ9 | X | X | X | X | X | X |
| Blood samples for clinical chemistry | X | X | X | X | X | X |
| Blood samples for biomarkers | X | X | X | X | X | X |
| Blood samples for genetics | X | |||||
Overview of blood samples obtained at all visits
| Clinical chemistry | Hemoglobin, white blood cells, differential white cell count, platelets, creatinine, urea, bilirubin, potassium, sodium, chloride, total calcium, phosphate, magnesium, CRP, albumin, triglycerides, vitamin-D |
| Inflammatory biomarkers | High-sensitivity CRP, IL-1β, IL-1, IL-1ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8/CXCL-8, IL-9, IL-10, IL-12 (p70), IL-13, IL-15, IL-17, basic fibroblast growth factor (bFGF), granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon-gamma (IFN-ɣ), eotaxin/CCL11, IFN-ɣ-inducible protein (IP-10)/CXCL10, MCP-1)/CCL2, MIP-1α/CCL3), MIP-1β/CCL4, regulated on activation, normal T-cell expressed and secreted (RANTES)/CCL5, TNF, platelet-derived growth factor (PDGF), and vascular endothelial growth factor (VEGF). |
| Biomarkers involved in bone remodelling | RANK-ligand (RANKL), Osteoprotegerin (OPG) and Notch Ligands: DLL1 and Periostin. |