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Abstract

Objective:

This study sought to assess the health-related quality of life and its predictors among patients diagnosed with prostate cancer in two municipalities in the Volta Region of Ghana and to compare the scores between patients receiving treatment and those not receiving treatment.

Methods:

A cross-sectional hospital-based analytical study was conducted among 205 prostate cancer patients attending 2 hospitals in the Volta Region. Health-related quality of life was measured using the functional assessment of cancer therapy-prostate instrument, comprising subscales for physical, emotional, social and functional well-being. Group differences were assessed using Kruskal–Wallis H tests, and multiple linear regression was used to identify predictors of overall health-related quality of life.

Results:

The performance under the individual domains or subscales was 14.8 ± 8.7, 14.1 ± 5.6, 13.7 ± 6.6, 9.6 ± 7.7, and 20.1 ± 9.9 for the physical well-being, social/family well-being, emotional well-being, functional well-being and PC subscales, respectively. The functional assessment of cancer therapy-trial outcome index was 44.6 (standard deviation ±16.2). The Functional Assessment of Cancer Therapy-General (FACT-G) total score among the study participants was 52.2 (standard deviation ±15.5). The participants in this study had an overall functional assessment of cancer therapy-prostate total score of 72 (standard deviation ±22), an indication of a lower health-related quality of life performance. Contrary to expectations, untreated patients reported slightly better scores in physical and emotional well-being and higher overall health-related quality of life scores compared to those who received treatment. Emotional well-being was significantly lower among treated patients (mean = 12.6) compared to untreated patients (mean = 16.9). Treated patients showed marginally better social and functional well-being. While differences in total scores between the groups were not statistically significant (p = 0.27), clinical variables such as urinary incontinence, pain, anxiety, erectile dysfunction and bowel problems were significantly associated with lower quality of life (all p < 0.001). Regression analysis identified older age (β = −0.12, p = 0.03), erectile dysfunction (β = −0.47, p < 0.001), bowel problems (β = −0.19, p < 0.001) and anxiety (β = −0.18, p < 0.001) as independent predictors of poorer scores, whereas being married was associated with higher performance on the scale (β = 0.13, p = 0.01).

Conclusion:

The functional assessment of cancer therapy-prostate scale revealed notably low health-related quality of life scores among men with prostate cancer in the two municipalities of Ghana’s Volta Region. Untreated patients reported better emotional and physical well-being, while treated patients had slightly better social and functional well-being. Overall scores were higher in untreated patients. Erectile dysfunction, bowel issues, anxiety and older age significantly reduced performance on the scale. Marriage positively predicted better quality of life outcomes. Clinical or symptom burden and psychosocial factors had a greater impact on overall quality of life than treatment status, emphasising the need for comprehensive care.

Keywords

FACT-P health-related quality of life prostate cancer predictors treatment well-being

Introduction

Prostate cancer (PCa), being a major cause of morbidity and mortality worldwide, is one of the most diagnosed cancers and the fifth leading cause of cancer death among men worldwide. Global estimates revealed close to 1,414,259 new cancer cases and 375,304 deaths in 2020 alone.¹ The condition is the most frequently diagnosed cancer in over 100 countries, and the leading cause of cancer death in close to 50 countries.² Despite the rising awareness and interventions to prevent PCa, the burden of the disease is expected to increase due to population ageing and economic growth across the globe.³

The burden of PCa in Ghana is underreported.⁴ Estimates from the middle belt of the country in 2015 indicate a rise in the prevalence rate of PCa amongst men, as PCa was second among all other forms of cancer in 2012 and first in 2015.⁵ This surge in disease burden is associated with late-stage diagnoses and a mortality rate of more than 80%.⁶ The incidence of PCa will continue to increase with the ageing of the Ghanaian population, and this has major public health and economic implications for the entire country.⁶ This is because, in Ghana, the cost of diagnosing and managing PCa is said to be overwhelming for the average Ghanaian.⁷ There has been a corresponding gradual increase in PCa screening, especially in urban areas in Ghana and many West African countries, with an anticipated increase in the number of men being diagnosed with localised PCa who may need treatment.⁸ For all these individuals in Ghana, and elsewhere, who are afflicted with PCa, their health-related quality of life (HRQoL) is significantly affected. HRQoL, therefore, is seen as a measure of multidimensional assessment of how a disease and treatment affect a patient’s sense of overall function and well-being HRQoL.⁹ HRQoL is an aspect of health which focuses on the impact of health on a person’s ability to live a fulfilling life. It embodies a broad perception of physical, psychological, with social functioning and well-being that includes both positive and negative dimensions.¹⁰ Therefore, beyond the general principle of expecting individuals with PCa to live healthy and longer lives, HRQoL is recognised as an important determinant of overall patient outcomes.¹¹

PCa has been reported to have a significant burden on HRQoL.¹² According to studies, men with PC encounter a variety of HRQoL problems, such as physical symptoms including pain and incontinence, mental anguish and social and sexual dysfunction.^13,14

The assessment of HRQoL in patients with PCa has received little attention in the medical literature, despite the severe negative effects of PCa on HRQoL.¹⁵ This is unexpected given the significance of HRQoL as a patient-centred outcome measure that offers important knowledge about how the disease and its treatment affect a person’s well-being.¹⁶ A further benefit of assessing HRQoL in patients with PC is that it can inform healthcare providers about the efficacy of various treatments and support measures aimed at enhancing HRQoL in these individuals.¹⁷ To ensure that patients with PCa receive optimal care and experience the best health outcomes, their HRQoL needs are to be assessed regularly.

Given these benefits, this study sought to assess the HRQoL and its predictors among patients diagnosed with PCa in two municipalities in the Volta Region of Ghana and to compare HRQoL scores between those receiving treatment and those not receiving treatment.

Materials and methods

Design

The study employed a cross-sectional hospital-based and analytical research design. It involved collecting data from a sample of patients diagnosed with PCa who attended the Sogakope District and Hohoe Municipal Hospitals between the periods from April to August 2023. The reporting of this study strictly followed the STROBE guideline.^18,19

Study setting

This research was conducted in two health facilities within two municipalities in the Volta Region, namely Sogakope District Hospital and the Volta Regional Hospital (formerly known as Hohoe Municipal Hospital). The two facilities are secondary-level health facilities under the Ghana Health Service with staff strength of about 328 and 342, respectively. The facilities render outpatient services, emergency services and inpatient services, which comprise the male, female and children’s wards, as well as surgical interventions (theatre). As of 2022, the doctor-to-patient ratio was 1:4183 and 1:4232, with a nurse-to-patient ratio of 1:181 and 1:201 in Sogakope District and the Hohoe Municipal Hospitals, respectively. In Sogakope Hospital, the number of patients attending the urology clinic in 2022 was 1874, with a diagnosis of 156 cases of PCa. This was against a total of 2634 outpatient attendants with 187 PCa cases diagnosed at the Hohoe Hospital. All patients attending the urology clinics in these two facilities are over the age of 40 years and are screened for PCa using prostate-specific antigen tests, digital rectal examination and ultrasound findings. Those with findings suggestive of PCa are further screened by a prostate biopsy to confirm the diagnosis.

Study population

The target population for the study comprised patients diagnosed with PCa at Sogakope District Hospital and Hohoe Municipal Hospital. Inclusion criteria were (1) a confirmed diagnosis of low-to moderate PCa risk, (2) diagnosis done within 12 calender months preceding the study, and (3) with or without initiation of PCa treatment since in Ghana, not all individuals diagnosed with PCa have the opportunity to receive treatment as sociocultural and economic barriers have been identified by previous studies to negatively impact PCa treatment uptake.²⁰ Patients were excluded if they had severe comorbidities, cognitive impairment, metastatic disease or other systemic complications.

Sample size estimation

The sample size was determined using the formula for estimating proportions,²¹ n = $\frac{Z^{2} p (1 - p)}{d^{2}}$ , and was estimated based on the Global Cancer Incidence, Mortality and Prevalence (GLOBOCAN) 2020 report in Ghana, with PCa prevalence of 14.1%, margin of error of 5%, the total minimum sample size was estimated to be 205 after 10% allocation for non-response.²²

Sampling procedure

Participants were chosen from the two hospitals by simple random sampling (lottery method) after being carefully screened to make sure they met the requirements for inclusion. They were enrolled one after the other until the target sample size per facility was met. To ensure good representation from both facilities, an allocation of samples was done proportional to size based on the past years’ urology clinic attendance, with a total of 2634 and 1874 for Hohoe and Sogakope, respectively. Hohoe was allocated 60% (123) and Sogakope, 40% (82). We used the simple random sampling procedure to recruit known PCa patients who reported to the clinic for review and passed the inclusion criteria.

Data collection instrument

The assessment of HRQoL of patients diagnosed with PCa was done using the functional assessment of cancer therapy-prostate (FACT-P) scales version 4.^23,24 The scale has been used widely and adapted to measure HRQoL of PCa in this study. The FACT-P questionnaire is a widely used instrument for measuring HRQoL in patients with PCa.^23,24 The questionnaire consists of 39 items measured on a 5-point Likert scale and organised into 4 domains: physical well-being (PWB), social/family well-being (SWB), emotional well-being (EWB), and functional well-being (FWB). The FACT-P also includes an additional subscale that assesses PCa-specific (PCS) symptoms.^23,24 The theoretical range of these scores is (0–156) for the FACT-P total score (0–108), for the functional assessment of cancer therapy-general (FACT-G) total score, and (0–104) for the FACT-P trial outcome index (TOI). The various subscales or domains we have (0–28) for the PWB and SWB (0–24), for EWB and (0–28) for FWB and finally (0–48) PCS. A higher score is an indication of a better HRQoL.^23,24

The FACT-P scale has undergone significant research to determine its psychometric qualities, which are widely regarded as strong. The questionnaire has been validated and has shown good psychometric properties with Cronbach’s alpha coefficients ranging from 0.68 to 0.89 for the four questionnaire domains and 0.75 for the PCS scale, indicating strong internal consistency.^25,26 Additionally, it has been demonstrated that the scale has strong construct validity and test–retest reliability.²⁷ The instrument also captured responses on sociodemographic variables such as age, marital status and employment status. In addition, clinical variables including PCa-related pain, erectile dysfunction and anxiety were assessed through self-reports using a dichotomous scale, with ‘Yes’ indicating the presence and ‘No’ indicating the absence of these conditions. The instrument also captured responses on sociodemographic variables such as age, marital status and employment status. In addition, clinical variables including PCa-related pain, erectile dysfunction, anxiety, incontinence and bowel problems were assessed through self-reports using a dichotomous scale, with ‘Yes’ indicating the presence and ‘No’ indicating the absence of these conditions.

Data collection procedure and techniques

Individuals who were officially diagnosed with PCa, met all the inclusion criteria and showed interest through the signing of the written informed consent form were allowed to take part in the HRQoL evaluation exercise. Participants were recruited as they presented to the urology clinic for review. During the data collection phase, the participants were made aware of the study’s objective, associated benefits, risks and results dissemination. Written informed consent forms were made available to the participants. We obtained informed consent from all the participants prior to data collection. The questionnaires (Supplementary Material) were administered in a face-to-face interview moderated by the principal investigator and his research assistants, who had undergone rigorous training in obtaining informed consent, random sampling, as well as how to interview study participants accurately. The interviews took place in the consulting rooms of the two study sites. Participants were interviewed serially to ensure their right to privacy was not violated. All source documents from the field were de-identified to ensure confidentiality. Each interview lasted for approximately 10–15 min.

Data analysis

Data was coded and analysed using STATA 21. Frequency distributions, proportions and percentages of all categorical variables were obtained. Means and standard deviations (SD) were computed for each item in the scale, and composite mean scores were computed for all the sub-scales of the HRQoL FACT-P scale. The FACT-P scoring guideline version 4 was used to assess the performance of the study participants under each sub-scale of the instrument. FACT-TOI was obtained by summing up PWB, FWB and PCS scores, with the obtainable scores ranging from 0 to 104. FACT-G total was obtained by summing up PWB, SWB, EWB and FWB scores, with obtainable scores ranging from 0 to 108. The FACT-P total was obtained by summing up the performance scores of all the sub-scales, giving a total obtainable score that ranges between 0 and 156, with a higher score indicating a better HRQoL among the participants.

A Kruskal–Wallis H test was utilised to compare the FACT-P Score across different demographic groups. The median (interquatile range (IQR)) was also presented for each group within the demographic variables.

A linear regression model was built and included various predictors such as age, marital status, PCa treatment, side effect experience, urinary incontinence, erectile dysfunction, bowel problems, pain experience and anxiety experience. The model summary showed an R² value of 0.523, indicating that approximately 52.3% of the variance in the FACT-P total score could be explained by the predictor variables included in the model. The adjusted R² value was 0.500. The ANOVA results revealed a statistically significant F-value (F = 23.144, p < 0.001). We set our level of significance at 0.05.

Ethical considerations

This study involves human subjects, and hence, it was done in accordance with the Helsinki Declaration (1975, 2024). Ethical Clearance for the study was obtained with clearance number GM/IRB/32/23. Permission was further obtained from the Sogakope District Health Directorate and Hohoe Municipal Health Directorate. The study’s nature and purpose were explained to participants, and thereafter, they voluntarily completed the consent process by signing the written informed consent forms. All source documents were de-identified using serial numbers and codes instead of participants’ names.

Results

The data in Table 1 provide descriptive statistics on the demographic characteristics of the 205 patients with PCa who were included in the study. Regarding age, the majority (91.2%) of the patients were 51 years or older, with only 8.8% between 46 and 50 years old. The largest group in reference to religion was Christians (68.5%). The education levels of the patients were relatively evenly distributed, with 30.2% having tertiary education, 29.8% having secondary education, 26.3% having no education and 13.7% having primary education. The current employment status showed that 33.7% of patients retired from active employment, 29.8% were self-employed, 26.3% were unemployed and only 10.2% were employed. The marital status of the patients revealed that the majority (78.9%) were married. A significant proportion (84.3%) owned their homes, while 15.7% lived in rented accommodations.

Table 1.

Sociodemographic characteristics of study participants.

Variable	Freq. (n)	Percent
Age (years)
46–50	18	8.8
51 and above	187	91.2
Religion
Christian	139	68.5
Islam	38	17.7
Traditionalist	28	13.8
Level of education
No education	54	26.3
Primary	28	13.7
Secondary	61	29.8
Tertiary	62	30.2
Current employment status
Employed	21	10.2
Retired	69	33.7
Self-employed	61	29.8
Unemployed	54	26.3
Total	205	100.0
Marital status
Single	8	3.9
Married	162	78.9
Divorced	18	8.8
Widowed	17	8.3
Residence
Self-owned	172	84.3
Rented	33	15.7
Availability of family support
Yes	180	87.8
No	25	12.2

Clinical characteristics of study participants

The result, as presented in Table 2, provides information about the clinical characteristics of the study participants. In terms of comorbidities, a significant proportion (50.2%) of the patients had hypertension, while 9.3% had both diabetes and hypertension. Additionally, 4.9% had diabetes only, 2.0% had stroke, and 1.0% had diabetes, hypertension, and stroke. The majority (76.5%) received treatment for PCa. Also, 53.4% of the study participants experienced side effects from their PCa treatment. Additionally, 67.3% of the patients reported experiencing pain related to their PCa or its treatment.

Table 2.

Clinical characteristics.

Variable	Freq. (n)	Percent
Comorbidities
None	67	32.7
Diabetes	10	4.9
Diabetes and hypertension	19	9.3
Diabetes, hypertension and stroke	2	1.0
Hypertension	103	50.2
Stroke	4	2.0
Receipt of treatment for PCa
Yes	156	76.5
No	48	23.5
Side effects from PCa treatment
Yes	109	53.4
No	96	46.6
Pain related to PCa or treatment?
Yes	138	67.3
No	67	32.7
Severity risk level^a
Minimally low risk	85	41.5
Low risk	66	32.2
Intermediate	34	16.6
Not sure	20	9.8
Duration of diagnosis in months
0–3	67	32.7
4–6	79	38.5
7–9	23	11.2
10–12	36	17.6

PCa: prostate cancer; PSA: prostate-specific antigen.

Minimally low risk > PSA < 5 ng/mL; low risk: PSA 5–10 ng/mL; intermediate risk: PSA 10–20 ng/mL.

Performance under the FACT-P total, FACT-TOI, FACT-G scale and five subscales

The result presented in Table 3 indicates the performance of the participants under the various subscales of the instrument and the overall HRQoL measure referred to as the FACT-P total score.

Table 3.

Quality of life performance among patients with PCa.

Scales	Mean (SD)	Median	Interquartile ranges
Scales	Mean (SD)	Median	25	50	75
PWB subscale score	14.8 (7)	15.0	10.0	15.0	20.0
SWB subscale score	14.1 (5.6)	13.0	10.0	13.0	17.0
EWB subscale score	13.7 (6.6)	16.0	9.0	16.0	19.0
FWB subscale score	9.6 (7.7)	7.0	3.0	7.0	15.0
PCS subscale score	20.1 (9.9)	19.0	13.0	19.0	27.5
FACT-P-TOI	44.6 (16.2)	44.0	33.0	44.0	55.0
FACT-G total score	52.2 (15.5)	50.0	41.0	50.0	60.5
FACT-P total score	72.4 (22.0)	69.0	57.0	69.0	85.0

SD: standard deviation; FACT-P: functional assessment of cancer therapy-prostate; FACT-G: functional assessment of cancer therapy-general; PWB: physical well-being; SWB: social/family well-being; EWB: emotional well-being; FWB: functional well-being; PCS: PCa-specific symptoms; PCa: prostate cancer; TOI: trial outcome index.

The performance under the individual domains or subscales is 14.8 ± 8.7, 14.1 ± 5.6, 13.7 ± 6.6, 9.6 ± 7.7 and 20.1 ± 9.9 for the PWB, SWB, EWB, FWB and PC subscales, respectively. The FACT-TOI was 44.6 (SD ±16.2), an indication of a lower performance compared to the maximum obtainable score of 104. The FACT-G total score among the study participants was 52.2 (SD ±15.5), an indication of a lower performance compared to the maximum obtainable score of 108. The participants in this study had an overall FACT-P total score of 72 (SD ±22), an indication of a lower HRQoL performance compared to the maximum obtainable score of 156.

Overall HRQoL performance across demographic groups

The results presented in Table 4 represent output from the Kruskal–Wallis H test for comparing the FACT-P scores across the various demographic groups, such as age, religion, marital status and education level. The performance of the entire scale across the various categories of the sociodemographic variables was not significant (p > 0.05), although the median FACT-P score differed within each group.

Table 4.

Overall quality of life performance across demographic groups.

Groups	FACT-P score, median (IQR)	N	Mean rank	H^a (df)	p-value
Age (n = 205)
Younger age	74.5 (65.3–90.0)	18	125.86	2.93 (1)	0.87
Older age	69.0 (56.0–82.00)	187	100.80
Religion (n = 203)
Christian	62 (60.0–62.0)	139	101.96	1.16 (2)	0.56
Islam	70.5 (58.0–83.5)	38	109.04
Traditionalist	67.0 (54.0–78.3)	28	93.13
Married status (n = 205)
Single	76 (59.5–108.3)	8	126.75	7.6 (3)	0.05
Married	69 (58.0–88.0)	162	106.63
Divorced	75 (54.8–81.0)	18	105.86
Widowed	57 (46.0–72.0)	17	67.35
Education (n = 205)
No education	61.5 (55–75.0)	54	88.33	6.03 (3)	0.10
Primary	76.0 (56.0–96.0)	28	111.52
Secondary	61.0 (70.0–82.0)	61	106.07
Tertiary	71.0 (57.5–94.0)	62	110.65

df: degree of freedom; IQR: interquatile range; FACT-P: functional assessment of cancer therapy-prostate.

Kruskal–Wallis test.

Overall HRQoL performance across clinical variable groups

As presented in Table 5, patients with only hypertension had a median FACT-P score of 70.0 (IQR: 60.0–86.0), while those with hypertension and diabetes scored 61.0 (53.0–88.0), and those with diabetes only scored 58.5 (49.5–83.5). Stroke patients had the highest score among comorbid groups, with a median of 80.0 (73.7–87.5). There was no significant difference in FACT-P scores across comorbidity groups (H(3) = 3.98, p = 0.26). Patients with urinary incontinence had significantly lower scores (median = 61.0, IQR: 52.0–61.0; mean rank = 77.11) than those without (median = 72.5, IQR: 58.8–92.0; mean rank = 111.57; H(1) = 12.9, p < 0.001). Those experiencing PCa-related pain had lower scores (median = 65.0, IQR: 54.7–76.0) than those without pain (median = 88.0, IQR: 66.0–100.0; H(1) = 26.9, p < 0.001). Anxiety or depression due to treatment was associated with lower scores (median = 60.5, IQR: 46.0–73.0) compared to those without distress (median = 74.0, IQR: 59.8–94.3; H(1) = 23.1, p < 0.001). FACT-P scores did not significantly differ between treated (median = 69.0, IQR: 55.0–81.8) and untreated patients (median = 71.0, IQR: 58.3–89.5; H(1) = 1.18, p = 0.27). Patients receiving family support had higher scores (median = 70.5, IQR: 57.3–86.8) than those who did not (median = 62.0, IQR: 51.5–69.5). This difference in family support was not statistically significant (H(1) = 3.2, p = 0.07). In summary, urinary incontinence, pain and psychological distress were significantly associated with lower HRQoL scores.

Table 5.

Overall HRQoL performance across clinical characteristics groups.

Groups	FACT-P score, median (IQR)	N	Mean rank	H^a (df)	p-value
Comorbidities
Hypertension only	70.0 (60.0–86.0)	103	71.41	3.98 (3)	0.26
Hypertension and diabetes	61.0 (53.0–88.0)	21	63.00
Diabetes only	58.5 (49.5–83.5)	10	53.45
Stroke	80.0 (73.7–87.5)	4	94.63
Urinary incontinence
Yes	61.0 (52.0–61.0)	51	77.11	12.9 (1)	0.00*
No	72.5 (58.8–92.0)	154	111.57
Pain related to PCa or treatment?
Yes	65.0 (54.7–76.0)	138	88.02	26.9 (1)	0.00*
No	88.0 (66.0–100.0)	67	133.85
Experienced anxiety/depression due to treatment
Yes	60.5 (46.0–73.0)	62	72.41	23.1 (1)	0.00*
No	74.0 (59.8–94.3)	142	115.64
Received treatment for PCa
Yes	69.0 (55.0–81.8)	156	100.01	1.18 (1)	0.27
No	710 (58.3–89.5)	48	110.59
Received support from family members
Yes	70.5 (57.3–86.8)	180	105.76	3.2 (1)	0.07
No	62.0 (51.5–69.5)	25	83.14

df: degree of freedom; FACT-P: functional assessment of cancer therapy-prostate; PCa: prostate cancer; IQR: interquatile range; HRQoL: health-related quality of life.

p < 0.05.

Kruskal–Wallis test.

Comparing the overall HRQoL performance among participants with PCa treatment and those without treatment

As presented in Table 6, EWB scores were lower among treated patients (mean = 12.6, SD = 6.7; median = 13.0) compared to untreated patients (mean = 16.9, SD = 4.7; median = 18.0). PWB was also slightly lower in the treated group (mean = 14.5, SD = 6.8; median = 14.0) than in the untreated group (mean = 15.6, SD = 7.5; median = 17.5). SWB was higher among those treated (mean = 14.4, SD = 5.3; median = 14.0) than untreated (mean = 13.2, SD = 6.1; median = 12.0). FWB showed a higher mean in the treated group (mean = 10.0, SD = 7.5; median = 8.0) than in the untreated group (mean = 8.5, SD = 8.2; median = 4.5). PCa subscale scores were similar across groups (treated: mean = 20.0, SD = 10.1; untreated: mean = 20.6, SD = 9.5). Both groups had similar TOI scores (treated: mean = 44.5, SD = 16.4; untreated: mean = 44.7, SD = 15.7). FACT-G total score was higher in the untreated group (mean = 54.4, SD = 13.3; median = 54.0) versus treated (mean = 51.5, SD = 16.1; median = 49.0). FACT-P total score was also higher in the untreated group (mean = 74.9, SD = 20.5; median = 71.0) versus the treated (mean = 71.1, SD = 22.5; median = 69.0). Untreated patients reported better emotional, physical, and general well-being. Treated patients scored slightly better on SWB and FWB scales.

Table 6.

HRQoL performance scales among PCa patients with treatment versus without treatment.

Scales	Received PCa treatment		No PCa treatment
Scales	Mean (SD)	Median	Mean (SD)	Median
PWB subscale score	14.5 (6.8)	14.0	15.6 (7.5)	17.5
SWB subscale score	14.4 (5.3)	14.0	13.2 (6.1)	12.0
EWB subscale score	12.6 (6.7)	13.0	16.9 (4.7)	18.0
FWB subscale score	10.0 (7.5)	8.0	8.5 (8.2)	4.5
PC subscale score	20.0 (10.1)	19.0	20.6 (9.5)	19.0
FACT-P_TOI	44.5 (16.4)	43.0	44.7 (15.7)	45.5
FACT-G total score	51.5 (16.1)	49.0	54.4 (13.3)	54.0
FACT-P total score	71.1 (22.5)	69.0	74.9 (20.5)	71.0

H(df) 1.18 (1) p = 0.27). SD: standard deviation; FACT-P: functional assessment of cancer therapy-prostate; FACT-G: functional assessment of cancer therapy-general; PWB: physical well-being; SWB: social/family well-being; EWB: emotional well-being; FWB: functional well-being; PCS: PCa-specific symptoms; PCa: prostate cancer; HRQoL: health-related quality of life; TOI: trial outcome index.

Predictors of overall HRQoL among patients with PCa

The results of multiple linear regression are presented in Table 7. The model investigated the factors influencing the FACT-P total, which represents the overall HRQoL of the participants. Several factors were found to be significant predictors of the HRQoL scores. Older age was found to be a significant predictor (β = 0.12; p = 0.03), with each unit increase in age associated with an average decrease of 9.53 points in the FACT-P total score, suggesting that older patients tend to report lower HRQoL scores. Being married was also a significant predictor (β = 0.13; p = 0.01), with married individuals exhibiting an average increase of 7.21 points in the FACT-P total score compared to those who were not married. Patients with erectile dysfunction have an average decrease of 26.50 points in their FACT-P score compared to those without erectile dysfunction (β = −0.47, p < 0.001). Patients with bowel problems have an average decrease of 9.19 points in their FACT-P score compared to those without bowel problems (β = –0.19, p < 0.001. Patients with anxiety have an average decrease of 8.84 points in their FACT-P score compared to those without anxiety (β = –0.18, p < 0.001).

Table 7.

Predictors of overall HRQoL among patients with PCa.

Variable	β	SE	95% CI for B, LL to UL	p	β
Older age (yes)	−9.53	4.39	−18.20 to 0.87	0.03*	−0.12
Married (yes)	7.21	2.80	1.69 to 12.73	0.01*	0.13
Current PCa treatment (yes)	5.62	3.31	−0.91 to 12.15	0.09	−0.11
Experience effect (yes)	−0.40	3.05	−6.41 to 5.62	0.90	−0.01
Urinary incontinence (yes)	−2.54	2.79	−8.05 to 2.96	0.36	−0.05
Erectile dysfunction (yes)	−26.50	3.41	−33.22 to −19.77	0.00*	−0.47
Bowel problems (yes)	−9.19	2.79	−14.69 to 3.70	0.00*	−0.19
Pain experience (yes)	−5.05	2.98	−10.94 to −0.83	0.09	−0.11
Anxiety experience (yes)	−8.84	2.63	−14.02 to 0.366	0.00*	−0.18

CI: confidence interval; SE: standard error; LL: lower limit; UL: upper limit; β: standardised coefficient; HRQoL: health-related quality of life; PCa: prostate cancer.

p < 0.05.

While receiving PCa treatment showed a positive effect on the FACT-P total score (an average increase of 5.62 points), this effect was not statistically significant at the 0.05 level (p = 0.09). Experiencing side effects from the treatment did not significantly impact the FACT-P score (p = 0.90).

Discussion

This study employed a cross-sectional hospital-based study approach and recruited men who were diagnosed with PCa in two municipalities in the Volta Region of Ghana. The study sought to determine the overall HRQoL, which is a patient reported outcome measure (PROM) and its associated predictors among the participants. PROMs represent important endpoints in PCa; therefore, obtaining clinically valid and accurate measurements of HRQoL of patients is essential in assessing patients’ perceived state of health and well-being. Second, a better understanding of the impact of the disease and the treatment on QoL is essential to guide patient care intervention programmes.

An accurate PROM measurement in this regard depends on validity and reliability as well as the effectiveness of the PROM measuring instrument to accurately communicate the patient’s perception of his well-being and overall health, and most importantly, to indicate the patient’s subjective experience with his disease and treatment. We therefore relied on the FACT-P scale, which has been tested and proven to have sound psychometric properties and is highly recommended to be used to assess the HRQoL of patients with PCa.²⁸

Performance of participants on HRQoL subscales and the overall FACT-P total scale

The results from our observational study showed that performance on all five domains was low, with corresponding low FACT-TOI, FACT-G scores and ultimately low FACT-P total score. This finding supports evidence from a systematic review and meta-analysis, which reported that 30 out of 52 studies that assessed HRQoL among patients with PCa reported overall lower HRQoL scores under the various domains.²⁹ The finding of our study, however, is divergent from reports on HRQoL assessment done among PCa patients in Finland, which also applied the 39-item FACT-P instrument and reported a considerably better performance across all five domains with a corresponding higher performance on the FACT-TOI, FACT-G and FACT-P scales.³⁰ Our FACT-P total score of 72.4 ± 22.0 is again far lower than the FACT-P total score of 110.8 ± 19.6 reported among Japanese men with PCa.³¹ The disparity in the HRQoL scores between the Ghanaian participants and those from Japan and Finland could probably be due to the developmental gap between these countries. It has been reported that developing countries have lower life expectancy and HRQoL compared to the developed, western and industrialised countries.³²

According to Obosi et al., HRQoL is a pointer to an individual’s functioning in everyday life as well as how the individual’s discernment of health status affects their life.³³ In this study, the findings point to the fact that the participants do not have very high and positive perceptions about their health and well-being, as well as their illness and treatment experiences are concerned.

Comparing HRQoL scores among treated and untreated participants

In the Ghanaian context, not all individuals with PCa have the opportunity to undergo treatment. Economic, social and health system barriers considerably influence the decision of people to receive cancer treatment.²⁰ For that reason, the study compared the HRQoL scores among men with PCa who received treatment with those without treatment. These findings present an interesting and somewhat counterintuitive pattern. While it might be expected that men undergoing treatment would report better QoL due to the clinical benefits of disease control and management, the untreated group reported higher scores in both EWB and PWB, and a slightly higher overall QoL (FACT-P total score). Similarly, in a tertiary hospital, Ramasubbu et al., applying the FACT-P scale, also reported worsening EWB among individuals receiving cancer treatment.³⁴ One possible explanation is the burden of side effects associated with treatment, such as fatigue, urinary incontinence or sexual dysfunction, which may offset perceived health gains.³⁵ For example, among Swedish participants, Ax et al. reported that cancer treatment affected the overall functioning in daily life, with limited activity and restricted participation.³⁶

It’s also possible that those who did not receive treatment had less advanced diseases to begin with, influencing both their actual well-being and their perception of it. Psychologically, individuals not undergoing treatment may feel a greater sense of autonomy or normalcy, unencumbered by the demands of medical care, as it has been reported that anxiety and depression are associated with PCa treatment.³⁷ Cultural narratives around illness and strength may also play a role; in some contexts, not pursuing treatment might be seen as a sign of resilience or optimism. However, the differences between groups are relatively small and reflect the observation that prospective evaluation seems to indicate that global HRQoL does not differ in men by treatment modality.³⁸ Therefore, these differences observed should be interpreted with caution, especially given the lack of a statistically significant difference observed in the treated and the untreated group in terms of the overall FACT-P Total score, as well as treatment not being a predictor of HRQoL in this study.

Predictors of HRQoL among men with PCa

The findings of this study suggest that anxiety negatively impacted the overall HRQoL of our study participants in that an increase in the level of anxiety reduced the FACT-P score by 8.84. This finding agrees with reports from a study done in Ghana that reported that men diagnosed with PCa have anxiety, distress and even suicidal ideations.³⁹ This perhaps could have contributed to the reduction in the state of their EWB, leading to a low overall HRQoL. It was also reported that the PWB of Ghanaian men diagnosed with PCa was negatively impacted by recurrence of symptoms, erectile dysfunction, use of indwelling catheters and fatigue.³⁹ These factors probably contributed to the low FWB score with a corresponding reduction in the total FACT-P.

In this study, we observed that erectile dysfunction predicted the level of HRQoL of the study participants. This observation agrees with what has been previously reported. According to Kinnaird et al., 94% of men being treated with androgen deprivation therapy for PCa experience erectile dysfunction, which is commonly referred to as the inability to get or keep an erection firm enough for satisfactory sexual intercourse.⁴⁰ Erectile dysfunction affects the social and PWB of patients with PCa and subsequently has psychological impacts⁴¹ and significant consequences for HRQoL.⁴²

The study also observed that older age predicted HRQoL, such that a unit increase in age produced a significant reduction in the overall FACT-P total score of the study participants. Our finding aligns with a systematic review of studies that assessed the predictors of HRQoL among patients with PCa and identified older age as a negative predictor of HRQoL among men with PCa.²⁹ Again, in Indonesia, a related study found that older adults reported a lower HRQoL score compared to younger adults.⁴³ It has been reported that older age is an unmodified factor in individuals especially those over 65 years old, and it has the tendency to reduces the QOL such that the most visible changes in HRQoL are evident during the transition from the seventh to the eighth life decade and are further noticeable at 80 years and over.⁴⁴

In this study, we found that bowel problems in the study participants negatively impacted the HRQoL. This finding agrees with what was reported among Korean patients that bowel/gastrointestinal disorders had a significant effect on the HRQoL of patients.⁴⁵ Bowel problems can considerably affect the PWB and FWB of patients with PCa and negatively affect their HRQoL.

In our study, marriage was identified as a positive predictor of HRQoL, such that being a married man increased the average FACT-P score by 7.21 units. Studies have reported the important role of marriage in HRQoL, especially for men. For example, a Korean study reported that single men had significantly worse HRQoL compared to married men.⁴⁶ Perhaps married men in this study receive companionship and support from their partners, and this can promote their social and EWB and thereby improve their overall HRQoL.

Contrary to the widely held view that cancer treatment improves the health-related HRQoL of patients, this study did not identify treatment as a significant predictor of HRQoL among men with PCa.⁴⁷ Instead, factors such as marital status, older age, erectile dysfunction and anxiety emerged as key predictors. These findings suggest that, beyond clinical treatment, psychosocial and demographic factors play a critical role in shaping the QoL of individuals diagnosed with PCa.

Study limitations, strengths and novelty

The cross-sectional design precludes any conclusions about causality or changes in HRQoL over time. The relatively small sample size from two secondary-level institutions may limit generalisability to other settings, especially rural or primary care centres. Furthermore, potential confounding variables such as cancer stage, comorbidities or time since diagnosis were not controlled for, which may influence HRQoL outcomes. Lastly, the study relied on self-reported data, which may be subject to recall or social desirability bias.

As a way of stating the strengths of this study, this study is one of the few studies in Ghana to quantitatively assess the HRQoL among men with PCa using the FACT-P tool. By comparing HRQoL scores between men on treatment and those not receiving treatment, the study provides early evidence of the nuanced impact of cancer therapies on patients’ well-being in this context. These insights are especially relevant as PC incidence rises in the region and healthcare systems grapple with balancing treatment efficacy, resource constraints and patient HRQoL.

Conclusion

This study examined HRQoL among men with PCa receiving care at Sogakope Hospital and Volta Regional Hospital in Ghana. Using the FACT-P instrument, we found that while overall HRQoL scores were low, men who were not receiving treatment reported slightly higher scores in EWB, PWB, and total FACT-P scores compared to those undergoing treatment. These findings suggest that treatment-related side effects such as fatigue, urinary dysfunction and psychological burden may negatively impact perceived HRQoL. In multivariable analyses, several factors significantly predicted HRQoL. Older age, erectile dysfunction, bowel problems and anxiety were independently associated with lower overall HRQoL, while being married was associated with better HRQoL. These results suggest that beyond PCa treatment, there is a complex interplay of clinical, psychosocial and demographic factors, and these factors are involved in shaping the lived experience of PCa. As Ghana and other sub-Saharan African countries expand access to PCa diagnosis and treatment, it is essential that patient-centred outcomes like HRQoL are integrated into care planning. Addressing modifiable factors such as anxiety, pain and sexual dysfunction through supportive care, counselling, and im-proved patient communication may enhance HRQoL and overall well-being for men living with PCa.

Supplemental Material

sj-docx-1-smo-10.1177_20503121251360120 – Supplemental material for ‘Beyond Treatment’: Clinical and psychosocial predictors of health-related quality of life of patients with prostate cancer

Supplemental material, sj-docx-1-smo-10.1177_20503121251360120 for ‘Beyond Treatment’: Clinical and psychosocial predictors of health-related quality of life of patients with prostate cancer by Michael Effah Ntiamoah and Vivian Efua Senoo-Dogbey in SAGE Open Medicine

Footnotes

Acknowledgements

We acknowledge the staff of Sogakope District Hospital and the Hohoe Municipal Hospital, and also the Research Departments of the District/Municipal Health Directorates for their collaborative efforts. We also express our special thanks to the Medical Superintendents of the Sogakope District Hospital and the Hohoe Municipal Hospital for their collaboration with the research team.

ORCID iD

Vivian Efua Senoo-Dogbey

Ethical considerations

Ethical Clearance for the study was duly obtained with clearance number GM/IRB/32/23 and permission was further obtained from the Sogakope District Health Directorate and Hohoe Municipal Health Directorate. The study’s nature and purpose were explained to participants, and thereafter, they voluntarily completed the consent process by signing the written informed consent forms. All source documents were identified using serial numbers instead of participants’ names.

Author contributions

Ntiamoah Effah Michael: Conceptualisation, Methodology, Software, Data curation, Writing, Original draft, Preparation, Visualisation, Investigation, Validation. Vivian Efua Senoo-Dogbey: Methodology, Investigation, Validation, Writing, Original draft, Preparation, Reviewing and editing.

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Data availability statement

Data are available from the corresponding author upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

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