Examining the influence of illness perception and financial toxicity on the quality of life of prostate cancer patients

Abstract

Background Cancer of the prostate (CaP) is a public health problem that affects the male genitourinary system causing a significant threat to men’s quality of life (QoL). Experiencing financial constraints and poor illness perception may further compromise the QoL of men with CaP. Methods Aim: To examine the relationship between financial toxicity and illness perception with quality of life in men with CaP. The descriptive cross-sectional study used simple random sampling technique to recruit 173 men with CaP from four tertiary health facilities in Nigeria. Data were collected with the comprehensive score for financial toxicity (COST-FACIT), the brief illness perception questionnaire (Brief IPQ) and the functional assessment of cancer therapy-prostate (FACT-P). Analysis of data was carried out using analysis of variance, correlation and hierarchical regression analyses. Results The 173 participants had an average age of 71.57 ± 11.18, and 53.18% had one comorbid disease. Significant difference was found in overall QoL based on treatment site and number of comorbid diseases (P < 0.01). QoL had a significant inverse relationship with all the illness perception variables and a significant linear relationship with lower financial toxicity (P < 0.01). Furthermore, financial toxicity (P < 0.05) and four illness perception variables: consequences, identity, concern and illness understanding (P < 0.01), had significant individual influences on QoL of men with CaP. Conclusions Quality of life in men with CaP may be improved through mitigating the financial toxicity associated with accessing care and providing appropriate counseling about the illness and what to expect following prostate cancer diagnosis and during treatment.

Comprehensive Score for Financial Toxicity and Health-Related Quality of Life in Patients With Cancer and Survivors: A Systematic Review and Meta-Analysis

“…Interestingly, our included studies showed that the correlation strengths between financial toxicity and overall HRQOL were slightly stronger in studies that used English instruments (median = 0.53, range = 0.33-0.73) 57,58,60,62,64,66,73,81 than those in other languages, for example, Mandarin Chinese, Italian, and Arabic (median = 0.43, range = 0.34-0.52), 51,55,67,72,79,80 and conducted in countries with universal health coverage (median = 0.49, range = 0.34-0.73) 55,58,66,72,79,80 than those without (median = 0.42, range = 0.33-0.63). 51,57,60,62,64,67,73,81 Nevertheless, we had inadequate number of studies to further examine (eg, performing subgroup analysis) the potential impact of instrument language or universal health coverage on the association between financial toxicity and HRQOL. 46 Exploring the role of universal health coverage and mitigation strategies in alleviating financial toxicity and improving HRQOL may be an important future research direction.…”

“…Akin-Odanye et al (2021) 51 Higher financial toxicity is associated with worse HRQOL -COST and FACT-P correlation: r = 0.416 (P , .010) -COST and FACT-P regression: B = 0.392, b = 0.181 (P , .…”

“…Nine studies reported financial toxicity as a significant predictor of HRQOL using multivariate regression models. [51][52][53]56,61,65,71,76,77 For instance, every 1-point increase in COST score, which indicated less financial toxicity, improved HRQOL scores measured with different instruments by 0.59 points (FACT-G), 71 0.47 points (University of Washington quality of life), 65 and 0.39 points (FACTprostate cancer). 49 All these regression models were adjusted for sociodemographic factors.…”

“…49 All these regression models were adjusted for sociodemographic factors. These included age, [51][52][53]56,58,61,65,71,76,77 employment status, 53,56,76,77 education, 51,53,76,77 race, 52,53,71 sex, 71,77 (loss of) income, 65,71 and marital status. 51,76 Furthermore, in several studies, the regression models were controlled for clinical variables, such as comorbidities, 51,61 cancer type, 71,76 cancer stage, 53,71 and cancer recurrence.…”

“…These included age, [51][52][53]56,58,61,65,71,76,77 employment status, 53,56,76,77 education, 51,53,76,77 race, 52,53,71 sex, 71,77 (loss of) income, 65,71 and marital status. 51,76 Furthermore, in several studies, the regression models were controlled for clinical variables, such as comorbidities, 51,61 cancer type, 71,76 cancer stage, 53,71 and cancer recurrence. 53,71 Four other studies estimated multivariate regression models differently by using HRQOL to predict financial toxicity.…”