Asian Pacific Journal of Cancer Prevention

Asian Pacific Journal of Cancer Prevention (아시아태평양암예방학회)
권호 표지
DOI QR코드

DOI QR Code

Determinants of Opioid Efficiency in Cancer Pain: a Comprehensive Multivariate Analysis from a Tertiary Cancer Centre

  • Goksu, Sema Sezgin (Kayseri State Hospital of Research and Education, Department of Medical Oncology) ;
  • Bozcuk, Hakan (Akdeniz University, Faculty of Medicine, Department of Medical Oncology) ;
  • Uysal, Mukremin (Afyon Kocatepe University, Faculty of Medicine, Department of Medical Oncology) ;
  • Ulukal, Ece (Akdeniz University, Faculty of Medicine) ;
  • Ay, Seren (Akdeniz University, Faculty of Medicine) ;
  • Karasu, Gaye (Akdeniz University, Faculty of Medicine) ;
  • Soydas, Turker (Akdeniz University, Faculty of Medicine) ;
  • Coskun, Hasan Senol (Akdeniz University, Faculty of Medicine, Department of Medical Oncology) ;
  • Ozdogan, Mustafa (Akdeniz University, Faculty of Medicine, Department of Medical Oncology) ;
  • Savas, Burhan (Akdeniz University, Faculty of Medicine, Department of Medical Oncology)
  • Published : 2014.11.28
Download PDF
⟨ Previous Next ⟩

Abstract

Background: Pain is one of the most terrifying symptoms for cancer patients. Although most patients with cancer pain need opioids, complete relief of pain is hard to achieve. This study investigated the factors influencing persistent pain-free survival (PPFS) and opioid efficiency. Materials and Methods: A prospective study was conducted on 100 patients with cancer pain, hospitalized at the medical oncology clinic of Akdeniz University. Patient records were collected including patient demographics, the disease, treatment characteristics, and details of opioid usage. Pain intensity was measured using a patient self-reported visual analogue scale (VAS). The area under the curve (AUC) reflecting the pain load was calculated from daily VAS tables. PPFS, the primary measure of opioid efficacy, was described as the duration for which a patient reported a greater than or equal to two-point decline in their VAS for pain. Predictors of opioid efficacy were analysed using a multivariate analysis. Results: In the multivariate analysis, PPFS was associated with the AUC for pain (Exp (B)=0.39 (0.23-0.67), P=0.001), the cumulative opioid dosage used during hospitalisation (Exp (B)=1.00(0.99-1.00), P=0.003) and changes in the opioid dosage (Exp (B)=1.01 (1.00-1.01), P=0.016). The change in VAS score over the standard dosage of opioids was strongly associated with current cancer treatment (chemotherapy vs. others) (${\beta}=-0.31$, T=-2.81, P=0.007) and the VAS for pain at the time of hospitalisation (${\beta}=-0.34$, T=-3.07, P= 0.003). Conclusions: The pain load, opioid dosage, concurrent usage of chemotherapy and initial pain intensity correlate with the benefit received from opioids in cancer patients.

Keywords

References

  1. Aslan FE, Kayis A, Inanir I et al (2011). Prevelance of cancer pain in outpatients registered to a cancer chemotherapy center in Turkey. Asian Pac J Cancer Prev, 12, 1373-5.
  2. Azevedo Sao Leao Ferreira K, Kimura M, Jacobsen Teixeira M (2006). The WHO analgesic ladder for cancer pain control, twenty years of use. How much pain relief does one get from using it? Support Care Cancer, 14, 1086-93. https://doi.org/10.1007/s00520-006-0086-x
  3. Brant JM (2010). The global experience of cancer pain. Asian Pac J Cancer Prev, 1, 7-12.
  4. Budkaew J, Chumworathayi B (2013). Knowledge and attitudes toward palliative terminal cancer care among Thai generalists. Asian Pac J Cancer Prev, 14, 6173-80. https://doi.org/10.7314/APJCP.2013.14.10.6173
  5. Colak D, Oguz A, Yazilitas D, Imamoglu IG, Altinbas M (2014). Morphine: patient knowledge and attitudes in the central Anatolia part of Turkey. Asian Pac J Cancer Prev, 15, 4983-8. https://doi.org/10.7314/APJCP.2014.15.12.4983
  6. Davis MP, Walsh D (2004). Epidemiology of cancer pain and factors influencing poor pain control. Am J Hosp Palliat Care, 21, 137-42. https://doi.org/10.1177/104990910402100213
  7. Fainsinger RL, Fairchild A, Nekolaichuk C et al (2009). Is pain intensity a predictor of the complexity of cancer pain management? J Clin Oncol, 27, 585-90.
  8. Fainsinger RL, Nekolaichuk CL, Lawlor PG et al (2005). A multicenter study of the revised Edmonton Staging System for classifying cancer pain in advanced cancer patients. J Pain Symptom Manage, 29, 224-7. https://doi.org/10.1016/j.jpainsymman.2004.05.008
  9. Fainsinger RL, Nekolaichuk CL (2008). A "TNM" classification system for cancer pain: the Edmonton Classification System for Cancer Pain (ECS-CP). Support Care Cancer, 16, 547-55. https://doi.org/10.1007/s00520-008-0423-3
  10. Gammaitoni AR, Fine P, Alvarez N et al (2003). Clinical application of opioid equianalgesic data. Clin J Pain, 19, 286-97. https://doi.org/10.1097/00002508-200309000-00002
  11. Green CR, Hart-Johnson T, Loeffler DR (2011). Cancer-related chronic pain: examining quality of life in diverse cancer survivors. Cancer, 117, 1994-2003. https://doi.org/10.1002/cncr.25761
  12. Jokela R, Ahonen J, Tallgren M et al (2008). Premedication with pregabalin 75 or 150 mg with ibuprofen to control pain after day-case gynaecological laparoscopic surgery. Br J Anaesth, 100, 834-40. https://doi.org/10.1093/bja/aen098
  13. Kanbayashi Y, Hosokawa T, Okamoto K et al (2011). Factors predicting requirement of high-dose transdermal fentanyl in opioid switching from oral morphine or oxycodone in patients with cancer pain. Clin J Pain, 27, 664-7. https://doi.org/10.1097/AJP.0b013e3182168fed
  14. Knudsen AK, Brunelli C, Kaasa S et al (2011). Which variables are associated with pain intensity and treatment response in advanced cancer patients?--Implications for a future classification system for cancer pain. Eur J Pain, 15, 320-7. https://doi.org/10.1016/j.ejpain.2010.08.001
  15. Liang SY, Chen KP, Tsay SL et al (2013). Relationship between belief about analgesics, analgesic adherence and pain experience in Taiwanese cancer outpatients. Asian Pac J Cancer Prev, 14, 713-6. https://doi.org/10.7314/APJCP.2013.14.2.713
  16. Liang SY, Wang TJ, Wu SF et al (2013). Gender differences associated with pain characteristics and treatment in Taiwanese oncology outpatients. Asian Pac J Cancer Prev, 14, 4077-82. https://doi.org/10.7314/APJCP.2013.14.7.4077
  17. Mercadante S, Gebbia V, David F et al (2011). Does pain intensity predict a poor opioid response in cancer patients? Eur J Cancer, 47, 713-7. https://doi.org/10.1016/j.ejca.2010.12.020
  18. Parruti G, Tontodonati M, Rebuzzi C et al (2010). Predictors of pain intensity and persistence in a prospective Italian cohort of patients with herpes zoster: relevance of smoking, trauma and antiviral therapy. BMC Med, 8, 58. https://doi.org/10.1186/1741-7015-8-58
  19. Thapa D, Rastogi V, Ahuja V (2011). Cancer pain management-current status. J Anaesthesiol Clin Pharmacol, 27, 162-8. https://doi.org/10.4103/0970-9185.81820
  20. van den Beuken-van Everdingen MHJ, de Rijke JM, Kessels AG et al (2007). Prevalence of pain in patients with cancer: a systematic review of the past 40 years. Ann Oncol, 18, 1437-49. https://doi.org/10.1093/annonc/mdm056
  21. Vandervaart S, Berger H, Tam C et al (2011). The effect of distant reiki on pain in women after elective Caesarean section: a double-blinded randomised controlled trial. BMJ, 1, 21.

Cited by

  1. A systematic review of the risk factors for clinical response to opioids for all-age patients with cancer-related pain and presentation of the paediatric STOP pain study vol.18, pp.1, 2018, https://doi.org/10.1186/s12885-018-4478-3