Sage Journals: Discover world-class research

Abstract

Introduction

Cancer patients’ quality of life (QoL) significantly influences treatment response and mortality rates. Understanding QoL domains among patients with cancer and what affects it can help create interventions that improve QoL and ease patients’ experience. This study measures the OoL among patients with cancer and influencing factors.

Methods

A prospective cross-sectional questionnaire-based study included cancer patients aged >18 currently receiving treatment. The questionnaire collected social and economic data, followed by the validated Arabic version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC-QLQ-C30). Means and standard deviations for described numeric variables and frequencies and percentages described categorical variables. Analysis of variance, F-tests, and P-values were reported.

Results

Among 182 cancer patients, 60% were female. Younger patients exhibited higher QoL in physical and role functioning (P = .016 and .03) and experienced more significant financial impact (P = .0144). Females reported more adverse effects from cancer symptoms, including fatigue, nausea, vomiting, and pain (36.7% vs 25.5%, P = .005; 20.6% vs 11.5%, P = .0186; 34.7% vs 25.1%, P = .0281). Single patients had superior QoL in physical functioning compared to others (P = .0127). Patients traveling long distances were more likely to face adverse financial consequences (P = .007). Asthmatic patients exhibited lower QoL in physical, role, and cognitive functioning (72.3 vs 37.8, P = .0147; 76.4 vs 22.2, P = .0024; 84.7 vs 44.4, P = .0038) and reported increased dyspnea and appetite loss (16 vs 55.6 and 26.1 vs 66.7, both P < .05).

Conclusion

Factors influencing QoL in Saudi cancer patients include age, marital status, gender, hospital distance, and chronic conditions. Thus emphasizing the necessity for personalized care strategies to enhance outcomes and alleviate the overall burden of cancer care.

Keywords

cancer quality of life Saudi patients cancer care cancer survival

Introduction

Cancer continues to be a striking global health concern, representing a substantial risk to individuals’ physical and mental health and serving as a primary cause of mortality globally. In contemporary times, there has been an upsurge in the frequency of cancer not only in Saudi Arabia but also in several other countries.^1-6 Given the escalating incidence of this ailment, it is imperative to comprehend its ramifications on the quality of life (QoL) of affected patients. Quality of life encompasses a holistic evaluation of an individual’s general welfare and capacity to engage in routine tasks and experience enjoyment in life. The emotional, physical, and psychological well-being of cancer patients may be significantly impacted by the detrimental impact of the disease and its treatment, underscoring the significance of evaluating and managing their QoL.^7-9

Several demographic factors have been shown to affect QoL among cancer patients, including age,^10,11sex,^10,12 distance traveled for care,^13,14 and financial difficulties.^15,16 In addition, several studies indicated an inverse relationship between QoL of chronic comorbidities among patients with cancer.^17,18 One study found that the cancer stage was associated with lower performance status among patients with rectal cancer.¹⁹

Lower performance status may be translated to more symptoms, such as pain and fatigue, which may affect QoL. The relationship between overall QoL and the cancer stage is not straightforward. The strong collinearity between cancer stage and cancer therapy makes it hard to distinguish whether the diminished QoL is due to cancer stage or cancer therapy. Studies either implicate cancer therapy,²⁰ or implicate cancer stage in affecting physical functioning domains.²¹ However, other studies found no differences in overall QoL by cancer stage.^22,23

The progress made in cancer therapies has resulted in enhanced rates of survival. However, it is crucial to consider the clinical efficacy of treatments and their influence on the QoL.^9,24,25 According to several studies, cancer treatment may result in various physical, emotional, and social obstacles, including but not limited to fatigue, discomfort, alterations in body image, anxiety, and challenges in adapting to social and occupational settings.²⁶ It is imperative to consider these factors to assist patients in sustaining a superior QoL throughout their cancer experience. The incidence of depression and anxiety is widespread among individuals diagnosed with cancer, and the rates of occurrence are contingent upon a multitude of factors, including the type of cancer, the stage of treatment, and the methodologies employed for assessment. A recent investigation in Saudi Arabia indicates a substantial prevalence of moderate to severe depression (57%) and anxiety (44%) among individuals who have survived breast cancer. These results underscore the need for psychosocial assistance to this population.²⁷

Evaluating QoL in individuals with cancer entails a comprehensive assessment of various aspects, like physical, psychological, social, and functional well-being. Several research studies have emphasized the adverse effects of decreased quality of life on the advancement of diseases and rates of survival. Moreover, cancer patients frequently encounter symptoms of fatigue, depression, and anxiety, emphasizing the necessity for comprehensive support and interventions to tackle these difficulties.^16,28 The quality of life of cancer survivors is influenced by the interrelated factors of their physical, mental, and social health. Notwithstanding the challenges associated with cancer management, many individuals exhibit adaptability and coping mechanisms. Survivors’ quality of life may be significantly enhanced by providing comprehensive survivorship care, support services, and personalized attention to their needs.^28-32

Research has indicated a significant occurrence of diminished QoL among cancer patients.^20,33-35 Based on a study conducted in Saudi Arabia, a substantial proportion of cancer patients, precisely 50.3%, reported a prevalence of poor overall QoL.³⁶ Incorporating patient-reported outcome measures may enhance communication, augment patient satisfaction, and facilitate the monitoring of treatment response. Given the region’s distinctive cultural, societal, and health care system attributes, it is imperative to undertake research endeavors to investigate the QoL of individuals with cancer in Saudi Arabia.

This study aims to measure and assess the QoL among patients with cancer in Saudi Arabia. The study augments the current knowledge of factors affecting the QoL of Saudi cancer patients by incorporating indicators such as social well-being, financial status, and treatment efficacy.

Methods

Design and Setting

This study was approved by the institutional review board of King Saud University Medical City, Riyadh, Saudi Arabia, on the 11^th of October 2020 (20/0718/IRB). This prospective cross-sectional study was conducted in the Cancer Center, King Saud University Medical City, Riyadh, Saudi Arabia, from October 2020 until October 2021. The reporting of this study conforms to STROBE guidelines.³⁷

Inclusion and Exclusion Criteria

All Patients above 18 years old who were admitted to the medical oncology day clinic (MODC) to receive their current chemotherapy cycle were included in the study. Patients were excluded if they were not on active treatment, were cognitively unable to respond to questions, or refused to participate in the study.

Sampling approach and sample size calculations

A previous study found that patients with cancer have a QOL score of 65 points on average, with a standard deviation of about 27 points.³⁸ Using a non-probability convenient sampling approach, the sample size calculation was designed to detect 6 or more points-change in the overall QoL with 80% power using an alpha level of .05. Based on the previous parameters 161 patients were the needed sample size.

Patient Identification

A team of 2 interviewers screened and approached all patients on active treatment in the outpatient clinics during the study period to avoid selection bias. Once a candidate was identified, the aim of the study was explained to the patient, and consent was obtained if they agreed to participate.

In addition, an introductory paragraph was written in Arabic explaining the study’s purpose and rationale to the participants. Verbal consent was taken from the patients, and it was explained to them that participation by answering the questionnaire questions is a form of consenting to participate in the study and getting access to patients’ files for research only. Patients’ confidentiality was always protected as patients’ medication record numbers were de-identified and undisclosed once the data was collected. The questionnaire was filled out during a standardized interview through the two interviewers to ensure consistency between responders and to limit response bias by reducing missing information. During the interview, the interviewers were trained to read the questions to the patients and ask for their responses without adding any words outside the questions except if the patient did not understand them.

Survey contents

In addition to demographic information, patients’ comorbidities, and current cancer treatment, subjects were asked about their income, distance traveled to the hospital, nationality, educational status, marital status, and the number of persons living with them.

The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC-QLQ-C30) was employed to measure the subject’s quality of life.³⁹ The primary investigator contacted EORTC and got permission to utilize the Arabic version for academic research. The EORTC-QLQ-C30 consists of multiple scales that measure different aspects of quality of life, including first, 5 functional scales-that measure physical, cognitive, emotional, social, and role; Second, 3 symptoms scales -that measure nausea and vomiting, fatigue, and pain; Third, 2 items that assess patients’ global health status. Lastly, single questions assessed diarrhea, constipation, insomnia, appetite, dyspnea, and the financial impact of cancer. Except for global health status, all scales were measured on a four-point scale: 1 not at all, 2 a little, 3 quite a bit, and 4 very much. Global health status was measured using a seven-point Likert scale from 1 (very poor) to 7 (excellent). Based on the manual of EORTC-QLQ-C30, all responses were linearly transformed to a 0-100 scale. The higher score represents better functionality and better QOL. On the other hand, in the symptom scales, the higher score represented worse symptoms.

Statistical Analysis

Descriptive statistics were done using means and standard deviation for all numeric variables and frequencies and percentages for all categorical variables. Analysis of variance was conducted, and both F test and P values were reported. To account for the multiple comparisons, Bonferroni adjusted significant levels were reported.⁴⁰ Lastly, all needed data was collected, and hence, there was no missing data. All data were prepared and analyzed using Microsoft Excel and STATA 17.⁴¹

Results

Baseline Characteristics of Cancer Patients

A total of 182 patients with cancer agreed to participate in the study. Only 2 patients refused to participate in the study. Around 40% of the sample was between 40 and 60 years old. Females constituted 60% of the subjects. Approximately 75% were married. About type cancer, 53.3% had chronic myelogenous leukemia (CML), followed by breast cancer 22%, colon 22%, lung 2.2%, and .5% pancreatic cancer. Among patients with solid tumors, the majority had metastatic cancer, 60%. In addition, around 46% reported a monthly income of more than 10 000 Saudi Riyals, followed by 23% who reported a monthly income of less than 10 000 but more than 5000. Diabetes Mellitus was the most prevalent comorbidity 20%, followed by hypertension 16%. Table 1 contains more details about the general characteristics of the subjects.

Table 1.

Baseline Characteristics of Patients With Cancers Who Came for Follow-Up at the Cancer Center, King Saud University Medical City (N = 182).

Baseline Characteristics	Frequency	Percentage
Age
Less than 30	11	6.0
30-39	36	19.8
40-49	39	21.4
50-59	39	21.4
60-69	42	23.1
70 or more	15	8.2
Female	111	61.0
Saudi	170	93.4
Educational status
Higher education	5	2.7
University degree	67	36.8
High school degree	36	19.8
Less than high school	74	40.7
Marital status
Single	17	9.3
Married	139	76.4
Separated	10	5.5
Widowed	16	8.8
Distance traveled to the hospital
Less than 100 kilometer	85	46.7
100 kilometer or more	97	53.3
Type of cancer
Breast	40	22.0
Chronic myelogenous leukemia	97	53.3
Colon	40	22.0
Lung	4	2.2
Pancreas	1	0.5
Stage of cancer for solid tumors only (n = 85)
I	11	12.9
II	9	10.6
III	14	16.5
IV	51	60.0
Monthly total income of the household (SAR)
Less than 5000	29	15.9
5000 to 10 000	42	23.1
More than 10 000	84	46.2
Refused	27	14.8
Hypertension	29	15.9
Diabetes mellitus	36	19.8
High cholesterol	10	5.5
Cardiac diseases	3	1.6
Asthma	3	1.6
Thyroid diseases	8	4.4
Employment status
Unemployed	37	20.3
Retired	88	48.4
Employed	57	31.3

Regarding chemotherapy regimens, the combination of Pertuzumab and Trastuzumab was the most common, 12.5% (n = 5). Imatinib was used among 53.6% of patients with CML (n = 52), followed by Dasatinib 32%(n = 31). The combination of Capecitabine and oxaliplatin was used by 55% of patients with colon cancer (n = 22). Table 2 shows all chemotherapy regimens used by the study cohort.

Table 2.

Chemotherapy Regimens Received by Study Cohort (N = 182).

Cancer Type	Therapy	Freq	Percent
Breast	Ado-trastuzumab emtansine	5	12.5
	Docetaxel	5	12.5
	Paclitaxel	5	12.5
	Pertuzumab/Trastuzumab	5	12.5
	Fluorouracil/Epidoxorubicin/Cyclophosphamide	4	10
	Docetaxel/Cyclophosphamide	3	7.5
	Trastuzumab	3	7.5
	Doxorubicin/Cyclophosphamide	2	5
	Docetaxel/Carboplatin	1	2.5
	Docetaxel/Trastuzumab	1	2.5
	Doxorubicin/Trastuzumab	1	2.5
	Epirubicin/Fluorouracil/Cyclophosphamide	1	2.5
	Epirubicin/Oxaliplatin/Capecitabine	1	2.5
	Paclitaxel/Carboplatin	1	2.5
	Trastuzumab/Paclitaxel/Gemcitabine	1	2.5
	Zoledronic acid	1	2.5
	Total	40	100
Chronic myeloid leukemia	Imatinib	52	53.61
	Dasatinib	31	31.96
	Nilotinib	10	10.31
	Ponatinib	2	2.06
	Bosutinib	1	1.03
	Imatinib/Capecitabine/oxaliplatin	1	1.03
	Total	97	100
Colon	Capecitabine/oxaliplatin	22	55
	Bevacizumab	3	7.5
	Cetuximab	2	5
	Leucovorin/fluorouracil/irinotecan/Bevacizumab	2	5
	Capecitabine/irinotecan/Bevacizumab	2	5
	Capecitabine/oxaliplatin/Bevacizumab	2	5
	Cetuximab/Capecitabine	1	2.5
	Docetaxel/Cyclophosphamide	1	2.5
	Leucovorin/fluorouracil/irinotecan/Cetuximab	1	2.5
	Leucovorin/fluorouracil/oxaliplatin/Cetuximab	1	2.5
	Gemcitabine/Carboplatin	1	2.5
	Panitumumab	1	2.5
	Trastuzumab/Capecitabine/oxaliplatin	1	2.5
	Total	40	100
Lung	Carboplatin/Pemetrexed	1	25
	Nivolumab	1	25
	Paclitaxel	1	25
	Paclitaxel/Pembrolizumab	1	25
	Total	4	100
Pancreas	Albumin-bound paclitaxel	1	100

Factors Affecting QoL in Cancer Patients

This study found that younger cancer patients had higher QoL in physical functioning and role-functioning domains than older patients (F = 6.77, P = .016 and F = 2.54, P = .03, respectively, Table 3). However, older patients had higher QoL in the emotional functioning domain than younger patients. The mean QoL score for younger patients (<30 years old) was 43.9, while older patients (>65 years old) had a mean score of at least 74 in the emotional functioning domain (F = 3.96, P = .002). Younger patients were also more likely to be financially impacted by cancer than older patients (F = 2,93, P = .0144). Male patients had higher QoL than female patients in physical functioning (79.2 vs 67.4, F = 10.31, P = .0016) and role functioning domains (83.8 vs 70.3, F = 8.64, P = .0037). Female patients were more likely to be negatively impacted by cancer symptoms, such as fatigue, nausea and vomiting, and pain (36.7 vs 25.5, F = 8.09, P = .005; 20.6 vs 11.5, F = 5.64, P = .0186; 34.7 vs 25.1, F = 4.9, P = .0281 respectively). There was no substantial difference in QoL between Saudi and non-Saudi patients. However, non-Saudi patients were more likely to experience a negative financial impact due to cancer (F = 7.13, P = .0083). Cancer patients who could not complete high school had the lowest QoL in physical and role functioning compared to patients with higher education levels. This difference was statistically significant (F = 8.96, P < .001 and F = 3.3, P = .0216, respectively). Single patients had the highest QoL score in physical functioning compared to patients who were married, separated, or widowed (F = 3.71, P = .0127). Patients who had to travel 100 kilometers or more to the hospital had a lower quality of life (QoL) in the cognitive functioning domain than patients who lived closer to the hospital. The mean cognitive functioning score for patients who traveled long distances was 79.7%, while the mean QoL score for patients who lived closer was 89%. This difference was statistically significant (F = 6.98, P = .009). Additionally, patients who traveled long distances were more likely to experience a negative financial impact due to cancer (F = 7.44, P = .007). Patients in households with 6 or more people also had a lower QoL in the cognitive functioning domain than those with fewer people. The mean QoL score for patients who lived in crowded households was 90.1, while the mean QoL score for patients who lived in less crowded households was 80.8 (F = 6.39, P = .0123). Patients with breast cancer reported more fatigue (40.6 vs 30.26, F = 5.02, P = .0263) and lower quality of life in the role-functioning domain than their peers without breast cancer (66.3 vs 78.2, F = 4.73, P = .0309). Patients with chronic myelogenous leukemia (CML) had lower social functioning scores and more fatigue than the patients without CML (70 vs 81.8, F = 7.70, and 37.6 vs 27.7, F = 6.54, respectively, both P < .05). Patients with a monthly income of less than 5000 Saudi Riyal reported having lower physical functioning scores and more symptoms like pain, nausea, and vomiting than patients with higher income. These findings were statistically significant (P < .05). Cancer patients with chronic diseases like hypertension, diabetes mellitus, and asthma had lower QoL in physical and role functioning. Patients with hypertension reported 57.7 in the physical functioning domain compared to 74.7 QoL points for those without hypertension (F = 12.4, P = <.001). Similarly, patients with hypertension reported 58.6 points in the role functioning domain compared to those without hypertension, who reported 78.8 in the same domain (F = 10.9, P = <.001). In diabetic cancer patients, patients with diabetes had lower physical and role functioning than their peers without diabetes (61.1 vs 74.4, F = 9.22 and 65.3 vs 78.1, F = 5.06, both P < .05, Table 3). Patients with cardiac diseases reported significantly more nausea, vomiting, and diarrhea than patients without cardiac diseases. In asthmatic patients, QoL was lower in Physical functioning (72.3 vs 37.8, F = 6.07, P = .015), role functioning (76.4 vs 22.2, F = 9.49, P = <.001), and cognitive functioning (84.7 vs 44.4, F = 8.61, P = .003). Moreover, they reported more dyspnea and appetite loss than other patients without asthma (16 vs 55.6, F = 6.96, and 26.1 vs 66.7, F = 4.85, both P < .05). Regarding employment status, employed patients had the highest score in the physical functioning domain of the QoL, with 80.2 points compared to unemployed and retired patients (F = 5.81, P = .004).

Table 3.

Analysis of Variance with Bonferroni Adjustment for Exploring Factors Associated with Quality of Life Different Domains (N=182).

Characteristics	Global health status & quality of life	Physical Functioning	Role Functioning	Emotional Functioning	Cognitive Functioning	Social Functioning	Financial	Fatigue	Nausea and Vomiting	Pain	Dyspnea	Insomnia	Appetite loss	Constipation	Diarrhea
Characteristics	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.	Mean±Std. dev.
Age
Less than 30	68.9±24.7	84.2±17.7	81.8±25.2	43.9±29.1	80.3±26.7	66.7±29.8	36.4±43.3	39.4±27.4	37.9±28	36.4±24.5	21.2±22.5	57.6±39.7	30.3±27.7	39.4±36	24.2±39.7
30-39	72.7±18.1	82.4±17	88±18.9	75.5±26.7	82.4±26.4	83.3±27	26.9±38.9	32.1±29.6	17.6±30.3	30.6±31	15.7±25.8	42.6±38.7	25±34.2	23.1±35.5	21.3±30
40-49	76.5±19.4	79.7±19.4	77.4±29.2	75±25.1	85.5±26.8	72.2±33.2	33.3±38.2	29.1±23.4	13.2±18.8	30.8±24	17.1±28.5	41.9±34.8	27.4±30.5	23.9±34.2	11.1±24.6
50-59	72.4±18.8	70.4±23	71.8±32	77.1±24.5	83.8±23.7	75.6±27.8	10.3±21.8	30.2±25.1	12.4±17	31.2±30.9	15.4±25.2	33.3±34.2	23.1±29.8	29.9±34.9	8.5±18.3
60-69	67.5±21.8	58.6±27.6	64.7±35.7	75.4±22	85.3±21.2	72.2±29.4	19.8±31.3	35.2±25.3	17.9±29.1	32.5±29	17.5±29.7	34.1±34.9	27.8±32	27±33.1	10.3±26
70 or more	67.8±19.6	60±30.4	76.7±36.6	84.4±23.5	84.4±20.4	90±19.7	8.9±26.6	34.1±34.2	20±29	23.3±33.8	15.6±17.2	40±40.2	33.3±41.8	17.8±24.8	20±27.6
F-Test, P-Value	1.01, 0.4124	6.77, 0.016	2.54,0.0303	3.96, 0.002	0.14, 0.9839	1.68, 0.1423	2.93, 0.0144	0.43, 0.8272	2.02, 0.0785	0.31, 0.9061	0.11, 0.9907	1.04, 0.3952	0.28, 0.9214	0.71, 0.6137	1.64, 0.1508
Sex
Male	71.5±19.1	79.2±21.3	83.8±25.2	77.9±26.3	83.6±25.7	78.6±26	23±34.5	25.5±23	11.5±21	25.1±25	13.6±22.2	37.1±35	21.6±30.4	32.4±34.7	13.1±26.1
Female	71.7±20.6	67.4±25.5	70.3±33.1	72.4±25.3	84.4±23.1	74.8±31	21.6±34.1	36.7±27.7	20.6±27.4	34.7±30.4	18.6±28.3	40.5±37.2	30±32.7	22.2±32.5	14.4±26.8
F-Test, P-Value	0.01, 0.9431	10.31, 0.0016	8.64,0.0037	2.04, 0.1554	0.05, 0.8241	0.76, 0.384	0.07, 0.791	8.09,0.005	5.64, 0.0186	4.90, 0.0281	1.59, 0.2091	0.39,0.5328	3.04, 0.0829	4.02, 0.0465	0.10, 0.7535
Saudi
No	76.4±21.3	81.1±13.6	76.4±29.7	77.8±20.8	86.1±26.4	75±25.1	47.2±38.8	36.1±28.1	25±31.4	38.9±32	8.3±20.7	33.3±37.6	19.4±33.2	25±28.9	2.8±9.6
Yes	71.3±19.9	71.4±25.1	75.5±31.1	74.3±26.1	83.9±24	76.4±29.4	20.4±33.3	32.1±26.4	16.5±25	30.4±28.5	17.3±26.5	39.6±36.3	27.3±32	26.3±34.1	14.7±27.1
F-Test, P-Value	0.73, 0.3933	1.76, 0.1858	0.01, 0.9228	0.20, 0.6534	0.09, 0.7617	0.02, 0.8751	7.13, 0.0083	0.26, 0.6128	1.26, 0.2629	0.98, 0.3237	1.31, 0.2547	0.33, 0.564	0.67, 0.4154	0.02, 0.8996	2.29, 0.132
Educational Status
Higher Education	71.7±13.9	73.3±17	73.3±27.9	76.7±25.3	90±14.9	80±29.8	26.7±36.5	44.4±34.2	13.3±18.3	36.7±38	33.3±33.3	46.7±50.6	33.3±33.3	46.7±50.6	0±0
University Degree	73.6±20.6	79.7±19.1	80.1±27.9	70.4±29.8	84.6±25.2	76.4±28.9	18.9±33.4	33.5±24	17.9±25	29.1±26.2	16.9±25.5	42.8±36.1	25.9±31.2	27.9±34.1	16.9±28.6
High School Degree	75±18.8	79.4±17.1	84.3±27	82.6±16.9	89.4±19.2	75±28.9	16.7±31.4	25.3±22.8	13±22.9	24.5±24.7	12±21.3	27.8±34.3	26.9±32.7	25±33.2	12±25.4
Less than High School	68.1±20.1	61.4±28.6	67.3±33.9	74.2±24.9	80.6±25.4	76.6±30	27.5±35.9	33.9±29.5	18.5±27.5	35.4±31.8	17.6±28.3	41±36	27±33	23.9±32.4	13.1±25.8
F-Test, P-Value	1.33, 0.2669	8.96, <0.001	3.3, 0.0216	1.81, 0.1476	1.20, 0.3128	0.05, 0.9842	1.14 ,0.3345	1.33, 0.2652	0.44, 0.7224	1.34, 0.2617	1.08, 0.3569	1.55, 0.2026	0.09, 0.9666	0.8, 0.495	0.83, 0.4789
Marital Status
Single	73±24.6	82.4±26.1	86.3±28.4	66.2±32.9	83.3±25	76.5±30.7	27.5±39.5	28.1±27.2	25.5±27.7	28.4±28.1	17.6±23.9	37.3±37	27.5±31.7	29.4±37	19.6±35.5
Married	72.7±19.5	73.2±23.3	76.3±29.6	75.7±25.5	83.1±25.4	75.4±29.2	20.9±33.2	33.4±26.3	15.1±24.7	29.7±27.4	16.5±26.4	38.1±36.7	26.6±31.6	26.4±33.7	14.6±26.7
Separated	66.7±19.6	60±33.3	76.7±32.6	80±19.7	95±8.1	80±29.2	43.3±41.7	23.3±18.5	10±14.1	36.7±33.1	13.3±23.3	26.7±26.3	23.3±31.6	10±22.5	3.3±10.5
Widowed	63.5±19	58.3±22.1	57.3±39	69.8±22.3	86.5±16.4	81.3±28.5	14.6±29.7	33.3±31.7	29.2±30.7	40.6±37.5	18.8±29.7	58.3±33.3	29.2±38.2	31.3±35.4	8.3±19.2
F-Test, P-Value	1.25, 0.2933	3.71, 0.0127	2.64, 0.0511	1.03, 0.3814	0.82, 0.4851	0.25, 0.8631	1.76, 0.1559	0.61, 0.6094	2.41, 0.0682	0.86, 0.4628	0.10, 0.9625	1.97, 0.1203	0.07, 0.9755	0.94, 0.4207	1.07, 0.3651
Distance Traveled to the Hospital
Less than 100 Kilometer	71±20.4	75.3±22.3	76.5±31.3	74.2±25.8	89±18.5	72.7±30.2	14.9±28.4	31.5±24.2	14.5±22.8	28±25.5	16.9±24.5	37.3±35.4	24.3±29.3	28.2±32.7	14.5±28.4
100 Kilometer or More	72.2±19.8	69.1±26.2	74.7±30.7	74.8±25.8	79.7±27.5	79.4±27.9	28.5±37.6	33.1±28.5	19.2±27.5	33.5±31.2	16.5±27.7	40.9±37.1	28.9±34.2	24.4±34.5	13.4±24.8
F-Test, P-Value	0.16, 0.6912	2.86, 0.0924	0.14, 0.7079	0.03, 0.8732	6.98, 0.009	2.37, 0.1253	7.44 , 0.007	0.16, 0.6853	1.57, 0.2114	1.64, 0.2014	0.01, 0.9249	0.45, 0.5011	0.92, 0.3398	0.59, 0.4446	0.08, 0.7792
Number of Persons living in the house
Less than 6	70.4±21.2	70.8±25.8	75±34.6	73.6±23.4	90.1±19.2	79.4±28.1	17.2±31.4	30±27	16.4±24.6	29.9±29.7	15.6±24.5	38.5±36.2	26.6±31	20.8±28.2	12.5±22.6
6 or more	72.2±19.4	72.7±24	75.8±28.9	75.1±27	80.8±25.8	74.6±29.6	24.9±35.5	33.6±26.2	17.4±26	31.5±28.3	17.2±27.1	39.5±36.4	26.8±32.7	29.1±36.1	14.7±28.4
F-Test, P-Value	0.34, 0.5627	0.23, 0.6346	0.03,0.8605	0.14, 0.7078	6.39, 0.0123	1.15, 0.2844	2.10, 0.149	0.76, 0.3853	0.06, 0.8075	0.12, 0.7295	0.16, 0.6936	0.03, 0.8588	0.001, 0.9563	2.52, 0.1141	0.28, 0.5958
Breast Cancer
No	71.9±19.7	73.5±24.2	78.2±29.3	74.6±26.6	83.6±25.1	77.5±27.9	23.2±35.3	30±26.4	16.5±26	29.1±28.2	16.7±26	38±35.4	26.3±32.5	27±33.9	14.3±26.7
Yes	70.6±21.3	66.7±25.6	66.3±35.1	74.4±22.7	85.8±20.2	72.1±33	18.3±30.1	40.6±25.4	18.8±23.6	37.5±29.9	16.7±27.2	43.3±39.4	28.3±30.7	23.3±33.1	12.5±25.8
F-Test, P-Value	0.12, 0.7249	2.44, 0.1199	4.73, 0.0309	0.001, 0.9631	0.28, 0.6005	1.07, 0.3031	0.64, 0.4244	5.02, 0.0263	0.23, 0.6303	2.69, 0.103	0,1	0.67, 0.4154	0.13, 0.7226	0.37, 0.5449	0.15, 0.7023
Lung Cancer
No	71.9±20	72.4±24.4	75.6±31	74.4±25.8	84.2±24.1	76.5±29.2	22.5±34.5	32.1±26.5	16.8±25.4	31.1±28.8	16.7±26.3	39.3±36.2	26.6±31.8	26±33.8	13.9±26.7
Yes	58.3±16.7	55±32.4	75±31.9	79.2±27.6	79.2±25	66.7±27.2	8.3±16.7	41.7±27.8	29.2±28.5	25±31.9	16.7±19.2	33.3±47.1	33.3±47.1	33.3±27.2	16.7±19.2
F-Test, P-Value	1.81, 0.18	1.97, 0.1625	0.001, 0.9715	0.13, 0.7173	0.17, 0.6818	0.44, 0.5057	0.67, 0.4151	0.5, 0.4787	0.93, 0.3363	0.17, 0.6765	0,1	0.11, 0.7449	0.17, 0.6782	0.18, 0.6691	0.04, 0.8345
Chronic myelogenous leukemia
No	72.2±21	69.2±23.5	71.6±31.8	72.9±25.8	87.5±19.1	70±29.9	15.7±28.4	37.6±22.8	16.1±23.5	29.2±26.7	12.9±23.6	34.9±38.1	26.7±31.6	26.7±33.3	15.3±28
Yes	71.1±19.2	74.5±25.4	79±29.9	75.9±25.7	81.1±27.5	81.8±27.4	27.8±37.8	27.7±28.6	17.9±27.1	32.5±30.5	19.9±27.9	43±34.3	26.8±32.5	25.8±34.2	12.7±25.2
F-Test, P-Value	0.12, 0.7316	2.14 ,0.1456	2.67,0.1042	0.62, 0.4335	3.19, 0.0757	7.70, 0.0061	5.87, 0.0164	6.56, 0.0113	0.22, 0.637	0.58, 0.4469	3.27, 0.072	2.25, 0.1355	0.001, 0.977	0.03, 0.8588	0.43 , 0.5136
Stage of Cancer for solid tumors only
I	75±15.8	77.6±14.1	77.3±29.1	71.2±28.5	83.3±19.7	69.7±32.3	12.1±27	36.4±24.9	13.6±24.5	33.3±33.3	9.1±21.6	30.3±43.3	33.3±36.5	33.3±39.4	12.1±22.5
II	76.9±21.6	73.3±21.6	77.8±33.3	74.1±32.7	92.6±16.9	75.9±36.4	11.1±23.6	43.2±20.4	22.2±16.7	33.3±34.4	7.4±14.7	48.1±47.5	22.2±28.9	22.2±33.3	7.4±22.2
III	64.3±20.3	74.8±16.8	64.3±35.7	66.7±26.8	91.7±19.3	71.4±21.1	4.8±17.8	42.1±26.2	17.9±22.1	36.9±29.4	26.2±29.8	38.1±41	35.7±27.6	23.8±24.2	19±31.3
IV	72.9±22	65.1±26.4	71.2±31.5	74.8±24.1	86.3±19.4	68.6±30.8	20.3±31.3	35.7±22.1	15±25	25.5±22.9	11.1±22.8	32.7±35	23.5±32.2	26.8±34.7	16.3±29.3
F-Test, P-Value	0.89, 0.4501	1.36,0.2618	0.47, 0.704	0.38, 0.7662	0.67, 0.5699	0.16, 0.9228	1.28, 0.2883	0.48, 0.7	0.30, 0.827	0.87, 0.4594	1.89, 0.1378	0.50, 0.6852	0.77, 0.5169	0.23, 0.8758	0.39, 0.764
Monthly Total Income of the Household (SAR)
Less than 5000	67±21.5	60.5±28.6	67.8±34.2	73±23.4	81±27	70.1±29	58.6±39.5	39.1±30.8	24.1±28.4	48.9±34.2	18.4±29	47.1±32.8	33.3±36.7	23±31	13.8±24.4
5,000 to 10,000	71.4±22.4	70.6±27.6	72.6±29.2	71±27.4	79.8±29.1	77±28.7	13.5±28.6	34.4±27.9	14.3±26.2	27.8±27.5	13.5±22.2	38.9±40.9	28.6±32.6	23.8±32.3	11.9±27.4
More than 10,000	74.5±19.2	77.9±18.1	81.9±27.6	77±25.3	87.9±19.8	78±28.6	11.9±24.1	29.4±22.2	12.5±18.1	26.2±24.3	16.7±24	36.1±34.4	23.4±28.2	27±34.1	15.5±26.6
Refused	67.9±16	68.1±28.4	68.5±36.8	74.1±27.4	82.1±24	76.5±32.1	28.4±36.6	31.3±31.3	27.8±35.5	31.5±31.1	19.8±34.9	40.7±38.5	27.2±37	30.9±38	12.3±28
F-Test, P-Value	1.43, 0.2351	4.24, 0.0064	2.45, 0.0652	0.55, 0.6509	1.38, 0.2509	0.53, 0.6601	19.12, <0.001	1.08, 0.3593	3.55, 0.0156	5.00, 0.0024	0.37, 0.7751	0.68, 0.5665	0.76, 0.5196	0.34, 0.7945	0.21, 0.8915
Hypertension
No	72.2±19.8	74.7±22.6	78.8±28	74.9±26.6	84.6±23.8	76.4±28.8	21.6±33.2	30.4±25.5	16.3±25	29.6±27.6	15.7±25.4	39.2±35.9	26.8±31.8	26.4±33.7	14.4±26.7
Yes	68.7±20.9	57.7±29.9	58.6±39.5	72.7±20.8	81±25.9	75.9±31	25.3±39.5	42.9±29.5	20.7±28.1	37.9±33.9	21.8±29.9	39.1±38.9	26.4±33.8	25.3±34.1	11.5±25.6
F-Test, P-Value	0.74, 0.3903	12.41,0.0005	10.90, 0.0012	0.18, 0.6755	0.55, 0.4611	0.01, 0.9328	0.29, 0.5928	5.62, 0.0188	0.71,0.4001	2.05, 0.1544	1.35, 0.2466	001, 0.9854	0.001, 0.9558	0.02, 0.8753	0.39, 0.5921
Diabetes Mellitus
No	71.9±19.2	74.7±23.5	78.1±29.3	73.2±27.1	83.1±25.2	76.4±29.3	23.5±34.6	31.8±26.2	16.7±25	30.4±28.6	17.1±26.6	40±36.9	28.1±31.7	25.3±33.3	14.4±26.5
Yes	70.6±23.4	61.1±26.1	65.3±35.5	80.1±18.2	88±18.5	75.9±28.6	16.7±32.4	34.6±28.1	18.5±27.5	33.3±29.5	14.8±24.5	36.1±34.2	21.3±33	29.6±35.4	12±26.6
F-Test, P-Value	0.11, 0.7361	9.22 ,0.0028	5.06, 0.0257	2.10, 0.1489	1.18, 0.2794	0.01, 0.935	1.16, 0.2831	0.31, 0.5774	0.15, 0.6969	0.31, 0.5804	0.22, 0.6367	0.32, 0.5706	1.3, 0.2557	0.47, 0.4953	0.23, 0.6353
High Cholesterol
No	71.8±20	72.8±24.6	76.3±30.6	74.6±26	83.9±24.1	76.8±28.6	22.3±34.2	31.7±26.2	16.5±24.8	30±28.6	16.1±25.6	38.6±36.3	26.4±31.7	25.4±33.2	13.2±25.4
Yes	69.2±20.1	59.3±22.3	63.3±35.8	74.2±22.7	86.7±24.6	66.7±37.7	20±35.8	43.3±30.7	26.7±35.3	46.7±27	26.7±34.4	50±36	33.3±38.5	40±41	26.7±41
F-Test, P-Value	0.16, 0.6919	2.84,0.0937	1.66, 0.1997	0.001, 0.9623	0.12, 0.7263	1.15, 0.284	0.04, 0.8378	1.83, 0.1784	1.52,0.2191	3.20, 0.0753	1.55, 0.2147	0.94, 0.3339	0.45, 0.5043	1.79, 0.1829	2.47, 0.1177
Cardiac Diseases
No	71.6±20	72.3±24.7	75.9±31	74.7±25.7	84.1±24.1	76.2±29.3	22.5±34.4	32±26.5	16.5±25.2	30.6±28.8	16.2±26.1	39.5±36.5	26.8±32	26.1±33.8	13.2±25.6
Yes	75±22	55.6±15.4	55.6±25.5	63.9±33.7	83.3±28.9	83.3±16.7	0±0	55.6±11.1	50±16.7	50±16.7	44.4±19.2	22.2±19.2	22.2±38.5	33.3±33.3	55.6±50.9
F-Test, P-Value	00.09, 0.7682	1.37, 0.2437	1.28, 0.26	0.52, 0.4711	0.001, 0.9578	0.18, 0.6735	1.28, 0.2589	2.36, 0.1264	5.24, 0.0232	1.34, 0.2482	3.49, 0.0635	0.67, 0.4154	0.06, 0.8061	0.14, 0.7121	7.82, 0.0057
Asthma
No	71.8±19.8	72.6±24.3	76.4±30.1	74.8±25.6	84.7±23.1	76.6±28.9	21.4±33.4	31.8±26.1	16.9±25.5	30.7±28.4	16±25.3	38.9±36.1	26.1±31.3	26.3±33.7	14.2±26.6
Yes	58.3±30	37.8±16.8	22.2±38.5	58.3±36.3	44.4±50.9	55.6±41.9	66.7±57.7	63±35.7	27.8±25.5	44.4±50.9	55.6±50.9	55.6±50.9	66.7±57.7	22.2±38.5	0±0
F-Test, P-Value	1.35, 0.2472	6.07,0.0147	9.49, 0.0024	1.21, 0.2724	8.61, 0.0038	1.55, 0.2147	5.29, 0.0226	4.14, 0.0433	0.54, 0.4624	0.67, 0.4138	6.96, 0.0091	0.62, 0.4324	4.85, 0.029	0.04, 0.8376	0.84, 0.3601
Thyroid Diseases
No	71.8±19.9	72.3±24.5	76±30.4	74.7±25.9	83.8±24.1	76.8±29.1	21.8±34.1	32.2±26.3	17±25.8	30.6±28.8	16.1±25.5	38.9±36.7	26.2±31.8	25.9±33.8	14.2±26.9
Yes	67.7±22	65.8±27	66.7±42.7	71.9±21.8	89.6±23.5	64.6±28.8	29.2±37.5	34.7±31.7	16.7±17.8	39.6±26.6	29.2±37.5	45.8±24.8	37.5±37.5	33.3±30.9	8.3±15.4
F-Test, P-Value	0.32, 0.5737	0.53,0.4689	0.69, 0.4076	0.09, 0.7652	0.44, 0.5089	1.35, 0.2462	0.35, 0.555	0.07, 0.7969	0.001, 0.9669	0.75, 0.3865	1.92, 0.1676	0.28, 0.5979	0.95, 0.3322	0.38, 0.5409	0.37, 0.5432
Employment Status
Unemployed	70±21.3	72.8±21.6	72.1±32.4	77.5±22.7	84.2±24.2	75.2±29	12.6±22.7	36±24.2	14.9±25.1	31.1±30.7	13.5±26.6	37.8±36.1	27.9±35.6	36.9±34.1	11.7±23.9
Retired	70.8±19.5	66.4±26.4	72±33.4	75.5±23.3	83.5±23.6	74.8±30.3	24.2±36.3	34.2±28.1	20.1±26.3	33.1±30.7	19.7±26.6	38.3±37	30.3±33.4	22.3±33	14.4±27.1
Employed	73.8±20.1	80.2±21.4	83.3±24.4	71.2±30.7	84.8±25.1	79.2±27.5	25.1±36.3	27.1±24.9	13.7±24.2	27.5±24.1	14±25.2	41.5±35.8	20.5±26.5	25.1±33.5	14.6±27.5
F-Test, P-Value	0.53, 0.5904	5.81,0.0036	2.68, 0.0715	0.78, 0.461	0.05, 0.9522	0.43, 0.6524	1.84, 0.162	1.71, 0.1835	1.24, 0.2909	0.67, 0.5138	1.15, 0.3192	0.17, 0.8431	1.68, 0.1897	2.53, 0.0827	0.16, 0.8513
Total	71.6±20	72±24.6	75.5±30.9	74.5±25.7	84.1±24.1	72±24.6	22.2±34.2	32.4±26.5	17±25.4	31±28.7	16.7±26.2	39.2±36.3	26.7±32	26.2±33.7	13.9±26.5

Lastly, Table 4 shows the overall QoL score associated with certain chemotherapy regimens in the study cohort. The overall QoL score was (mean = 71.79 ± standard deviation (SD) = 19.54) among patients with CML who were on imatinib. On the other hand, CML patients on Dasatinib had slightly higher overall QoL scores (mean ± SD:73.12 ± 18.09); however, this was not statistically significant (P = .7587).

Table 4.

Overall QoL Score for Selected Chemotherapy Regimens Among the Study Cohort.

Cancer Type	Therapy	Freq	Mean ± Standard Deviation
Breast	Ado-trastuzumab emtansine	5	65±20.75
	Docetaxel	5	68.33±25.95
	Paclitaxel	5	68.33±22.36
	Pertuzumab/Trastuzumab	5	61.67±13.94
	Fluorouracil/Epidoxorubicin/Cyclophosphamide	4	81.25±4.67
	Docetaxel/Cyclophosphamide	3	63.89±17.35
	Trastuzumab	3	91.67±8.33
	Doxorubicin/Cyclophosphamide	2	70.83±17.67
Chronic myeloid leukemia	Imatinib	52	71.79±19.54
	Dasatinib	31	73.12±18.09
	Nilotinib	10	56.67±17.03
	Ponatinib	2	75±11.79
Colon	Capecitabine/oxaliplatin	22	76.14±21.41
	Bevacizumab	3	63.89±20.97
	Cetuximab	2	95.83±5.89
	Leucovorin/fluorouracil/irinotecan/Bevacizumab	2	45.83±17.67
	Capecitabine/irinotecan/Bevacizumab	2	83.33±23.57
	Capecitabine/oxaliplatin/Bevacizumab	2	66.67±23.57

Discussion

This study involved patients with active cancer currently receiving treatment. Several factors were associated with QoL in cancer patients in Saudi Arabia. These factors encompass age, education level, gender, marital status, distance to hospital, household size, cancer type, and chronic comorbidities. It has discovered several variables that seem to be linked to cancer patients’ quality of life. Previous research has also established a correlation between age, level of education, economic position, and quality of life.⁴² The research findings provide valuable insights into the factors that impact the QoL of persons diagnosed with cancer. Younger patients with cancer experienced higher QoL in physical functioning and role-functioning domains compared to their older peers. These findings align with previous research indicating that younger patients often exhibit better physical resilience and functional capacity, which may positively influence their QoL during cancer treatment and survivorship.^10,43,44 Younger individuals may have fewer comorbidities and better physical fitness, making them better equipped to cope with the physical challenges posed by cancer and its treatments. On the other hand, older cancer patients tend to have higher rates of comorbidities. They may experience more limitations in their physical functioning, potentially contributing to lower QoL scores in this domain. Nonetheless, it is crucial to consider that the specific type and stage of cancer, as well as the treatment regimen, may significantly impact physical functioning across all age groups.

In contrast to younger patients, older cancer patients reported higher QoL scores in the emotional functioning domain. These results may be attributed to various factors, including emotional resilience, coping strategies, and the psychological impact of a cancer diagnosis. Past studies have demonstrated that younger individuals have a remarkably diminished level of well-being, marked by worse physical, social, and emotional functioning when contrasted with older individuals.^10,11 Similarly, past studies have demonstrated that younger partners had heightened levels of disease intrusiveness and worse emotional well-being and employed less effective dyadic coping methods.¹⁰ The coping strategies shown by younger couples were impacted by their behaviors and their partners’ actions.⁴⁵ This implies that a heightened degree of reliance existed within their connection. The current investigation coincides with past studies, which revealed that the link between mutuality and quality of life in younger patients and older couples was mediated by suboptimal dyadic coping.^45-47

The study’s findings reveal prominent gender disparities in QoL within the physical functioning and role functioning domains. Male patients had significantly higher physical and role-functioning QoL scores than their female counterparts. These differences may be attributed to various factors. The study also highlights gender differences in the experience of cancer-related symptoms. Female patients were more likely to be negatively impacted by common cancer symptoms, such as fatigue, nausea and vomiting, and pain, than male patients. These gender disparities in symptom burden are consistent with existing research that has documented higher symptom reporting among female cancer patients.¹² Biologically, hormonal differences between men and women may play a role in the variation in symptom experiences.^48-50 For instance, hormonal fluctuations, particularly in the case of breast and gynecological cancers, may contribute to symptoms such as fatigue and nausea. Psychosocial factors may also contribute to these gender differences. Women often report higher levels of psychological distress and may be more inclined to express their symptoms and seek support.⁵¹ Social roles and expectations may shape how individuals perceive and communicate their symptom experiences, with men potentially underreporting symptoms.

The research results did not demonstrate a statistically significant variance in the quality of life between patients of Saudi descent and those of not. However, persons who were not of Saudi Arabian nationality demonstrated a greater likelihood of experiencing negative financial repercussions due to their diagnosis of cancer. This highlights the need to create financial support programs for non-Saudi patients since these efforts may significantly improve their overall QoL. These findings have several implications for health care providers and policymakers. Also, it is essential to address the specific needs of cancer patients who are at higher risk for poor QoL.

Individuals who did not get a high school education saw a decline in their QoL regarding physical well-being and their ability to fulfill societal roles. The observable effects of education on health literacy and access to health care services are noteworthy. Ensuring enough assistance and knowledge on managing their disease is crucial for patients with lower levels of education. This finding aligns with a previous study that reported that individuals with lower levels of education diagnosed with urinary cancer had worse physical, social, and role functioning, as well as advanced incidence of side effects.⁵² Studies have revealed a negative correlation between health literacy and physical functioning in older individuals.^53,54 The correlation between inadequate understanding, misinterpretations, and ineffective physician communication has been established in noncompliance with cancer therapy.⁵⁵

The study’s findings suggest that those who were not married had a higher degree of physical functioning, indicating a superior quality of life. This study’s findings suggest that individuals not involved in a committed partnership may encounter improved physical well-being, which might be attributed to a decreased load of caring obligations. However, the study did not explore the emotional aspects of being single and how they impact an individual’s quality of life (QoL). Previous research findings have demonstrated that those who are married have a greater level of life satisfaction and possess a more extensive social network consisting of family and friends. Studies have demonstrated that older individuals experience a diminished quality of life when their social network is limited. Research has also revealed strong correlations between perceptions of social connectedness and other mental health markers, including sadness, loneliness, and life satisfaction.⁵⁶

This study revealed that patients with extensive trips to the hospital reported a worse quality of life regarding their cognitive functioning. The result highlights the need to support those facing travel challenges, such as fatigue and stress, since these variables might influence their cognitive functioning. This discovery underscores the significance of health care service accessibility, particularly for individuals afflicted with chronic ailments such as cancer. Extended travel lengths have the potential to induce heightened levels of stress and weariness and hinder the availability of prompt medical assistance, hence exerting adverse impacts on cognitive performance. To alleviate the challenges faced by patients who must travel significant distances, health systems, and governments should prioritize enhancing infrastructure, providing transportation assistance, and expanding health care facilities. Our finding is in coherence with several past studies that have repeatedly demonstrated that the geographical distance 1 must travel to access health care services may significantly influence an individual’s overall well-being, cancer stage, and satisfaction with life.^13,14,57 Studies have indicated that extended trip durations are linked to postponed identification of medical conditions, diminished availability of prompt medical interventions, and heightened levels of stress and anxiety experienced by patients.^58,59 Numerous scholarly investigations have proposed implementing telemedicine, establishing local clinics, and providing transportation assistance programs as potential measures to alleviate the adverse impacts of extended journey lengths on the overall welfare of patients.¹⁵

Patients who undertook extensive journeys were shown to have a higher likelihood of encountering adverse financial consequences due to their cancer diagnosis. This finding underscores individuals’ complex and diverse difficulties in undertaking extensive journeys to get health care services. In addition to the physical and cognitive challenges, individuals frequently have financial difficulties.^15,16 The financial strain experienced by these people may be intensified due to increased expenses related to transportation, accommodation, and probable income loss, amplifying the overall adverse effects of their health condition.^15,16

Previous studies found a negative correlation between higher levels of financial load and quality of life (QOL).^15,16 This association is more pronounced regarding physical health than mental health. Additionally, those experiencing higher financial burdens tend to exhibit higher levels of nonspecific psychological distress. The aforementioned financial factors underscore the necessity of implementing financial aid initiatives, travel subsidies, or insurance policies to mitigate the cost burden experienced by individuals.

The observed disparity in average Quality of Life (QoL) ratings between those residing in densely populated homes and those in less densely populated households is a notable discovery with several implications. The cognitive performance of individuals living in densely crowded households was significantly reduced, leading to a poorer QoL. The cohabitation of a significant number of people nearby may lead to increased levels of stress and fewer chances for personal privacy, therefore impacting the cognitive well-being of individuals with cancer. Implementing supportive interventions for patients dwelling in such environments is paramount.^60-62

According to Koumarianou et al. (2021), implementing supportive interventions, such as providing resources for family counseling or enhancing living circumstances, may effectively alleviate the adverse consequences of overcrowded homes on individuals' quality of life (QoL).⁶³ Potential approaches to tackle these challenges involve facilitating individuals' access to housing assistance, offering family counseling services, and giving mental health support. These intrusions enhance patients' overall quality of life and psychological welfare.

Our study results showed that people diagnosed with breast cancer exhibit elevated levels of exhaustion and a worse quality of life, particularly in role performance. Similarly, individuals diagnosed with chronic myelogenous leukemia (CML) have reduced social functioning and increased levels of fatigue. Fatigue is a common phenomenon throughout the populace. Still, it is notably intensified in those who have received a cancer diagnosis, as shown by the investigations conducted by Ericsson et al (2013) and Neefjes et al (2013).^46,47 The occurrence of fatigue among individuals who have survived cancer is not restricted solely to the timeframe immediately following the diagnosis and treatment. Therefore, it is essential to detect the presence of fatigue by asking patients about it and teaching them about possible interventions to overcome it. For instance, psychosocial fatigue education and support programs that tackle fatigue-related thoughts and behaviors showed a reduction in the incidence of fatigue compared to standard care.^64-66 In addition, acupressure has shown promising results in fatigue reporting among patients with cancer.^67,68

Multiple studies worldwide and a few in Saudi Arabia have demonstrated that individuals who have successfully overcome cancer frequently report experiencing fatigue, irrespective of age, gender, or treatment modality.^13,48 It is essential to conduct customized interventions to effectively address the symptoms and concerns that are encountered by persons who have been diagnosed with various types of cancer. Earlier studies have discovered that those diagnosed with colorectal cancer had the highest quality of life, while those with lung cancer experienced the lowest levels. Breast cancer patients exhibited a significant prevalence of depression, negatively impacting their social interactions, role functioning, and overall quality of life.^49,50 Hair loss, altered body image, diminished sexual functions and libido, and reduced quality of social life were observed as side effects resulting from breast cancer, primarily due to early menopause.^49,50 Individuals diagnosed with head-neck and sarcoma conditions may have exacerbated bodily alterations due to their illnesses.

The present study findings indicate that individuals who have received a diagnosis of Chronic Myeloid Leukemia (CML) have worse scores in social functioning and elevated levels of weariness compared to individuals who do not have this diagnosis. Chronic Myeloid Leukemia (CML) management may exert various physical and mental burdens on individuals, potentially leading to social isolation and difficulties in maintaining an active social life. The potential manifestation of unfavorable outcomes aggravates the constraints above. Our findings are consistent with earlier research that highlights the need to provide psychological support and interventions tailored to the specific needs of persons diagnosed with Chronic Myeloid Leukemia (CML) to promote their social well-being.⁶⁹ Moreover, the emotional and psychological consequences linked to the phenomenon of living with a chronic cancer condition like Chronic Myeloid Leukemia (CML) may substantially add to feelings of exhaustion. Installing exercise programs or counseling services is crucial in improving the overall quality of life for chronic myeloid leukemia (CML) patients by effectively managing exhaustion.⁶⁹

Comorbid chronic illnesses affect cancer patients’ quality of life (QoL), which is crucial to their health.⁷⁰ The coexistence of anxiety and hypertension had considerably lower QoL ratings compared to those who didn’t.⁷¹ This shows the necessity of treating hypertension in cancer patients for better health. Several studies have shown that hypertension negatively impacts QoL, underlining the necessity for comprehensive therapy for both disorders.^72-76 Our study also demonstrated that cancer patients with diabetes also had worse physical and role functioning. A previous study found that diabetes was linked to a lower QoL for breast cancer survivors.⁷⁷ Diabetes has been demonstrated to increase tiredness and physical limits in cancer patients, lowering QoL. Our study has demonstrated that patients with heart problems had higher nausea, vomiting, and diarrhea and decreased quality of life. Cardiovascular disorders may complicate cancer therapy and cause side effects, lowering QoL. Previous investigations have shown that cardiac disorders might cause treatment-related problems, requiring frequent monitoring and supportive measures.⁷⁸ Study findings also revealed that cancer patients with asthma had worse physical, role, and cognitive QoL. Such findings about the impact of chronic conditions on QoL necessitate the need for integrative oncology care, which may improve QoL and fulfill patients’ needs.⁷⁹

The study also highlighted that younger cancer patients were more likely to be financially impacted by cancer compared to older patients. Financial toxicity in cancer care is a growing concern, as the cost of treatments and supportive care may lead to significant economic hardships for patients and their families.^15,80 Although the treatment is free of charge in SA, younger patients may be particularly vulnerable to financial distress due to their potentially more significant economic responsibilities and lower income stability than older patients. Prior studies have repeatedly demonstrated a robust correlation between income levels and diverse health outcomes. Individuals with lower socioeconomic status are more likely to have a greater prevalence of chronic illnesses, limited health care accessibility, and worse overall health outcomes. The topic of income-related health inequalities has been thoroughly examined in various studies conducted.^81,82

The provision of financial aid and the accessibility of affordable health care services play a vital role in improving the quality of life for those diagnosed with cancer, particularly those facing financial limitations. Individuals who have received a diagnosis of chronic diseases, such as hypertension, diabetes, and asthma, have been seen to experience a decrease in their overall quality of life, particularly in their physical well-being and their capacity to carry out their various duties and responsibilities effectively.¹⁵

In comparing the current results with Asian countries, the mean global health status among patients with breast cancer in this study was 70.6 (SD = 21.3), which was higher than what was measured among Indian women in the sub-Himalayan region (64.4 ± 29.7) but not statistically significant.⁸³ All functional scales in this study were higher than those reported among Bangladeshi patients with cancer, which was also reflected by the low global health status score of 48.85 (SD = 19.38).⁸⁴ On the other hand, a study that was conducted in Nepal reported a higher mean global health status among Nepali cancer patients (83.3 ± 17.70) despite a high mean financial burden score (68.02 ± 33.81).⁸⁵

This study has a few limitations. First, the small sample size might hinder addressing the association between QoL and patient status. Second, the sample included patients receiving both oral and intravenous agents. Both routes of administration may be burdensome on the patients with various side effects. However, oral anticancer agents might have a limited impact on social factors affecting the patient’s QoL. Determining the prevalence of features associated with a decreased quality of life posed significant challenges, primarily due to the vast array of psychological and clinical factors associated with this drop. Lastly, the significant heterogeneity between chemotherapy regions that the study cohort took reduced the ability to study the impact of chemotherapy regimens on QoL. Subsequent research endeavors have to consider a sufficient sample size to comprehensively evaluate the psychological and clinical variables linked with a reduced QoL among persons diagnosed with cancer.

Despite the limitations outlined, this study provides valuable insights into the QoL encountered by those diagnosed with cancer and the diverse array of factors that impact it. By incorporating these factors in health care, there is potential to boost the well-being and overall health outcomes of patients, particularly those with cancer.

Conclusion

Age, gender, education level, marital status, distance to hospital, household size, cancer type, and chronic comorbidities were factors associated with the QoL of Saudi cancer patients. Policymakers and health care providers should routinely evaluate the effect of cancer care on patients’ QoL to improve the outcomes and prevent unwanted associated burdens.

Footnotes

Acknowledgement

The authors are thankful to the Researchers Supporting Project Number (RSP2023R115) at King Saud University, Riyadh, Saudi Arabia for supporting this research.

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.

Funding

The research was funded by Researchers Supporting Project Number (RSP2023R115) at King Saud University, Riyadh, Saudi Arabia.

Ethical Statement

ORCID iDs

Mohammad H. Aljawadi

Muneeb U. Rehman

References

AlJaffar

Enani

Almadani

Albuqami

Alsaleh

Alosaimi

. Determinants of quality of life of cancer patients at a tertiary care medical city in Riyadh, Saudi Arabia. Front Psychiatry. 2023;14:1098176. doi:10.3389/fpsyt.2023.1098176.

Alqahtani

Almufareh

Domiaty

, et al. Epidemiology of cancer in Saudi Arabia thru 2010-2019: a systematic review with constrained meta-analysis. AIMS Public Health. 2020;7(3):679-696. doi:10.3934/publichealth.2020053.

Althubiti

Nour Eldein

. Trends in the incidence and mortality of cancer in Saudi Arabia. Saudi Med J. 2018;39(12):1259-1262. doi:10.15537/smj.2018.12.23348.

Chaudhri

Fathi

Hussain

Hashmi

. The increasing trends in cases of the most common cancers in Saudi Arabia. J Epidemiol Glob Health. 2020;10(4):258-262. doi:10.2991/jegh.k.200515.001.

Herzallah

Antonisamy

Shafee

Al-Otaibi

. Temporal trends in the incidence and demographics of cancers, communicable diseases, and non-communicable diseases in Saudi Arabia over the last decade. Saudi Med J. 2019;40(3):277-286. doi:10.15537/smj.2019.3.23585.

Jazieh

Da'ar

Alkaiyat

, et al. Cancer incidence trends from 1999 to 2015 and contributions of various cancer types to the overall burden: projections to 2030 and extrapolation of economic burden in Saudi Arabia. Cancer Manag Res. 2019;11:9665-9674. doi:10.2147/cmar.S222667.

Firkins

Hansen

Driessnack

Dieckmann

. Quality of life in “chronic” cancer survivors: a meta-analysis. J Cancer Surviv. 2020;14(4):504-517. doi:10.1007/s11764-020-00869-9.

Mokhtari-Hessari

Montazeri

. Health-related quality of life in breast cancer patients: review of reviews from 2008 to 2018. Health Qual Life Outcomes. 2020;18(1):338. doi:10.1186/s12955-020-01591-x.

Schütte

Schulz

Middelberg-Bisping

. Impact of gastric cancer treatment on quality of life of patients. Best Pract Res Clin Gastroenterol. 2021;50-51:101727. doi:10.1016/j.bpg.2021.101727.

10.

Arraras

Nolte

Liegl

, et al. General Spanish population normative data analysis for the EORTC QLQ-C30 by sex, age, and health condition. Health Qual Life Outcomes. 2021;19(1):208. doi:10.1186/s12955-021-01820-x.

11.

Alpert

Siddiqui

Shabbir

Soudan

Garren

. The role of psychiatry in quality of life in young patients with non-small cell lung cancer. Brain Behav Immun Health. 022;25:100507. doi:10.1016/j.bbih.2022.100507.

12.

Unger

Vaidya

Albain

, et al. Sex differences in risk of severe adverse events in patients receiving immunotherapy, targeted therapy, or chemotherapy in cancer clinical trials. J Clin Oncol. 2022;40(13):1474-1486. doi:10.1200/jco.21.02377.

13.

Virgilsen

Møller

Vedsted

. Travel distance to cancer-diagnostic facilities and tumour stage. Health Place. 2019;60:102208. doi:10.1016/j.healthplace.2019.102208.

14.

Alsultan

Aljefri

Ayas

, et al. Travel burden and geographic access to health care among children with cancer in Saudi Arabia. East Mediterr Health J. 2020;26(11):1355-1362. doi:10.26719/emhj.20.020.

15.

Edward

Bowling

Chitwood

Vanderpool

. Availability and accessibility of cancer care delivery approaches to reduce financial toxicity of rural and urban cancer patients in Kentucky. J Oncol Navig Surviv. 2022;13(5):156-164.

16.

Jones

SMW

Ton

Heffner

Malen

Cohen

Newcomb

. Association of financial worry with substance use, mental health, and quality of life in cancer patients. J Cancer Surviv. 2023;17(6):1824-1833. doi:10.1007/s11764-022-01319-4.

17.

Arneja

Brooks

. The impact of chronic comorbidities at the time of breast cancer diagnosis on quality of life, and emotional health following treatment in Canada. PLoS One. 2021;16(8):e0256536. doi:10.1371/journal.pone.0256536.

18.

H-S

Davis

Chen

. Impact of comorbidity on symptoms and quality of life among patients being treated for breast cancer. Cancer Nurs. 2019;42(5):381-387. doi:10.1097/ncc.0000000000000623.

19.

Cihan

Ozturk

. The effect of demographic, clinical, and pathological data on quality of life in rectum cancer. Support Care Cancer. 2021;29(12):7411-7420. doi:10.1007/s00520-021-06300-y.

20.

Ramprasad

Atchison

, et al. Quality of life in patients with recurrent and Second primary head and neck cancer. Otolaryngol Head Neck Surg. 2023;168(2):196-202. doi:10.1177/01945998221087712.

21.

Shahjalal

Sultana

Gow

, et al. Assessing health-related quality of life among cancer survivors during systemic and radiation therapy in Bangladesh: a cancer-specific exploration. BMC Cancer. 2023;23(1):1208. doi:10.1186/s12885-023-11670-z.

22.

Techata

Muangmool

Wongpakaran

Charoenkwan

. Effect of cancer stage on health-related quality of life of patients with epithelial ovarian cancer. J Obstet Gynaecol. 2022;42(1):139-145. doi:10.1080/01443615.2021.1877647.

23.

Nayak

George

Vidyasagar

, et al. Quality of life among cancer patients. Indian J Palliat Care. 2017;23(4):445-450. doi:10.4103/ijpc.Ijpc_82_17.

24.

Grusdat

Stäuber

Tolkmitt

, et al. Routine cancer treatments and their impact on physical function, symptoms of cancer-related fatigue, anxiety, and depression. Support Care Cancer. 2022;30(5):3733-3744. doi:10.1007/s00520-021-06787-5.

25.

Mehta

Kommalapati

Kim

. The impact of ramucirumab treatment on survival and quality of life in patients with gastric cancer. Cancer Manag Res. 2020;12:51-57. doi:10.2147/cmar.S199827.

26.

Salvetti

Machado

CSP

Donato

SCT

Silva

AMD

. Prevalence of symptoms and quality of life of cancer patients. Rev Bras Enferm. 2020;73(2):e20180287. doi:10.1590/0034-7167-2018-0287.

27.

Abu-Helalah

Mustafa

Alshraideh

, et al. Quality of life and psychological wellbeing of breast cancer survivors in the kingdom of Saudi Arabia. Asian Pac J Cancer Prev. 2022;23(7):2291-2297. doi:10.31557/apjcp.2022.23.7.2291.

28.

Hazard-Jenkins

. Breast cancer survivorship-mitigating treatment effects on quality of life and improving survival. Obstet Gynecol Clin North Am. 2022;49(1):209-218. doi:10.1016/j.ogc.2021.11.008.

29.

Esser

Mehnert-Theuerkauf

. [Cancer survivorship care programs and self-management]. Onkologe. 2021;27(8):766-770. Cancer-Survivorship-Care-Programme und Selbstmanagement. doi:10.1007/s00761-021-00945-4

30.

Franzoi

Agostinetto

Perachino

, et al. Evidence-based approaches for the management of side-effects of adjuvant endocrine therapy in patients with breast cancer. Lancet Oncol. 2021;22(7):e303-e313. doi:10.1016/s1470-2045(20)30666-5.

31.

Gebauer

Baust

Bardi

, et al. Updated international guidelines for survivorship care after pediatric cancer: practice implications in a German and Austrian comprehensive care network. Oncol Res Treat. 2023;46(9):382-389. doi:10.1159/000530970.

32.

Nekhlyudov

Mollica

Jacobsen

Mayer

Shulman

Geiger

. Developing a quality of cancer survivorship care framework: implications for clinical care, research, and policy. J Natl Cancer Inst. 2019;111(11):1120-1130. doi:10.1093/jnci/djz089.

33.

Aboufaras

Selmaoui

Ouzennou

. Quality of life of patients with cancer at the beni mellal oncology center. Value Health Reg Issues. 2024;41:86-93. doi:10.1016/j.vhri.2023.12.002.

34.

Rosenberg

O'Neill

Sepucha

, et al. Quality of life following receipt of adjuvant chemotherapy with and without bevacizumab in patients with lymph node-positive and high-risk lymph node-negative breast cancer. JAMA Netw Open. 2022;5(2):e220254. doi:10.1001/jamanetworkopen.2022.0254.

35.

Blakely

Chanson

Wong

, et al. Health-related quality of life and oncologic outcomes after surgery in older adults with colorectal cancer. Support Care Cancer. 2020;28(6):2857-2865. doi:10.1007/s00520-019-05087-3.

36.

Almutairi

Mansour

Vinluan

. A cross-sectional assessment of quality of life of breast cancer patients in Saudi Arabia. Publ Health. 2016;136:117-125. doi:10.1016/j.puhe.2016.03.008.

37.

von Elm

Altman

Egger

Pocock

Gøtzsche

Vandenbroucke

. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61(4):344-349. doi:10.1016/j.jclinepi.2007.11.008.

38.

Alshehri

Alzamil

Alturki

, et al. Quality of life of patients with cancer attending outpatient clinics at the king abdulaziz medical city, Riyadh, Saudi Arabia. Journal of Nature and Science of Medicine. 2020;3(1):53-58.

39.

Life TEOfRaToCQo . Eortc QLQ-C30. 23/2/2024. https://qol.eortc.org/questionnaires/core/eortc-qlq-c30/. Accessed 23 2 2024.

40.

Dunn

. Multiple comparisons among means. J Am Stat Assoc. 1961;56(293):52-64. doi:10.2307/2282330.

41.

Stata Statistical Software. Version Release 18. College Station, TX: StataCorp LLC; 2021.

42.

Montazeri

Hole

Milroy

McEwen

Gillis

. Quality of life in lung cancer patients: does socioeconomic status matter? Health Qual Life Outcomes. 2003;1:19. doi:10.1186/1477-7525-1-19.

43.

Catto

JWF

Downing

Mason

, et al. Quality of life after bladder cancer: a cross-sectional survey of patient-reported outcomes. Eur Urol. 2021;79(5):621-632. doi:10.1016/j.eururo.2021.01.032.

44.

Quinten

Coens

Ghislain

, et al. The effects of age on health-related quality of life in cancer populations: a pooled analysis of randomized controlled trials using the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 involving 6024 cancer patients. Eur J Cancer. 2015;51(18):2808-2819. doi:10.1016/j.ejca.2015.08.027.

45.

Acquati

Kayser

. Dyadic coping across the lifespan: a comparison between younger and middle-aged couples with breast cancer. Front Psychol. 2019;10:404. doi:10.3389/fpsyg.2019.00404.

46.

Park

Lee

Hwang

. Quality of life differences between younger and older breast cancer patients. J Breast Cancer. 2011;14(2):112-118. doi:10.4048/jbc.2011.14.2.112.

47.

Puciato

. Socio-economic conditions of physical activity of manual workers from Wrocław. Appl Econ Lett. 2016;23(12):831-834. doi:10.1080/13504851.2015.1111983.

48.

Al Maqbali

. Cancer-related fatigue: an overview. Br J Nurs. 2021;30(4):S36-S43. doi:10.12968/bjon.2021.30.4.S36.

49.

Ruiz-Casado

Álvarez-Bustos

de Pedro

Méndez-Otero

Romero-Elías

. Cancer-related fatigue in breast cancer survivors: a review. Clin Breast Cancer. 2021;21(1):10-25. doi:10.1016/j.clbc.2020.07.011.

50.

Thong

MSY

van Noorden

CJF

Steindorf

Arndt

. Cancer-related fatigue: causes and current treatment options. Curr Treat Options Oncol. 2020;21(2):17. doi:10.1007/s11864-020-0707-5.

51.

Peters

Brederecke

Franzke

de Zwaan

Zimmermann

. Psychological distress in a sample of inpatients with mixed cancer-A cross-sectional study of routine clinical data. Front Psychol. 2020;11:591771. doi:10.3389/fpsyg.2020.591771.

52.

Levinsen

AKG

Kjaer

Thygesen

, et al. Social inequality in cancer survivorship: educational differences in health-related quality of life among 27,857 cancer survivors in Denmark. Cancer Med. 2023;12(19):20150-20162. doi:10.1002/cam4.6596.

53.

Smith

O'Conor

Curtis

, et al. Low health literacy predicts decline in physical function among older adults: findings from the LitCog cohort study. J Epidemiol Community Health. 2015;69(5):474-480. doi:10.1136/jech-2014-204915.

54.

Hirooka

Kusano

Kinoshita

Aoyagi

. Association of health literacy with the prevalence of cardiovascular diseases and their risk factors among older Japanese health management specialists. Gerontol Geriatr Med. 2023;9:23337214231189059. doi:10.1177/23337214231189059.

55.

Puts

MTE

Tourangeau

, et al. Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review. Ann Oncol. 2014;25(3):564-577. doi:10.1093/annonc/mdt433.

56.

Kahn

Hessling

Russell

. Social support, health, and well-being among the elderly: what is the role of negative affectivity? Pers Indiv Differ. 2003;35(1):5-17. doi:10.1016/S0191-8869(02)00135-6.

57.

Tarnasky

Olivere

Ledbetter

Tracy

. Examining the effect of travel distance to pediatric cancer centers and rurality on survival and treatment experiences: a systematic review. J Pediatr Hematol Oncol. 2021;43(5):159-171. doi:10.1097/mph.0000000000002095.

58.

Thomas

Gallagher

O'Céilleachair

Pearce

Sharp

Molcho

. Distance from treating hospital and colorectal cancer survivors' quality of life: a gendered analysis. Support Care Cancer. 2015;23(3):741-751. doi:10.1007/s00520-014-2407-9.

59.

Konerding

Bowen

Elkhuizen

, et al. The impact of travel distance, travel time and waiting time on health-related quality of life of diabetes patients: an investigation in six European countries. Diabetes Res Clin Pract. 2017;126:16-24. doi:10.1016/j.diabres.2017.01.014.

60.

Brennan-Cook

Cadavero

. Professional case management in outpatient settings for patients with myeloproliferative neoplasms. Prof Case Manag. 2022;27(6):271-276. doi:10.1097/ncm.0000000000000584.

61.

Uemoto

Yamanaka

Kataoka

, et al. Efficacy of telemedicine using videoconferencing systems in outpatient care for patients with cancer: a systematic review and meta-analysis. JCO Clin Cancer Inform. 2022;6:e2200084. doi:10.1200/cci.22.00084.

62.

Kelly

Gordon

Thompson

Semple

. Availability and use of web-based interventions for patients with head and neck cancer: a scoping review. J Cancer Surviv. 2023;17(5):1309-1326. doi:10.1007/s11764-022-01168-1.

63.

Koumarianou

Symeonidi

Kattamis

Linardatou

Chrousos

Darviri

. A review of psychosocial interventions targeting families of children with cancer. Palliat Support Care. 2021;19(1):103-118. doi:10.1017/s1478951520000449.

64.

Yates

Aranda

Hargraves

, et al. Randomized controlled trial of an educational intervention for managing fatigue in women receiving adjuvant chemotherapy for early-stage breast cancer. J Clin Oncol. 2005;23(25):6027-6036. doi:10.1200/jco.2005.01.271.

65.

Armes

Chalder

Addington-Hall

Richardson

Hotopf

. A randomized controlled trial to evaluate the effectiveness of a brief, behaviorally oriented intervention for cancer-related fatigue. Cancer. 2007;110(6):1385-1395. doi:10.1002/cncr.22923.

66.

Poort

Peters

van der Graaf

WTA

, et al. Cognitive behavioral therapy or graded exercise therapy compared with usual care for severe fatigue in patients with advanced cancer during treatment: a randomized controlled trial. Ann Oncol. 2020;31(1):115-122. doi:10.1016/j.annonc.2019.09.002.

67.

Özdemir

Taşcı

. Acupressure for cancer-related fatigue in elderly cancer patients: a randomized controlled study. Altern Ther Health Med. 2023;29(4):57-65.

68.

Lin

Zhang

Qian

, et al. Auricular acupressure for cancer-related fatigue during lung cancer chemotherapy: a randomised trial. BMJ Support Palliat Care. 2021;11(1):32-39. doi:10.1136/bmjspcare-2019-001937.

69.

Flynn

Atallah

. Quality of life and long-term therapy in patients with chronic myeloid leukemia. Curr Hematol Malig Rep. 2016;11(2):80-85. doi:10.1007/s11899-016-0306-5.

70.

Benzo

Moreno

Fox

, et al. Comorbidity burden and health-related quality of life in men with advanced prostate cancer. Res Sq. 2023;rs.3:2572781. doi:10.21203/rs.3.rs-2572781/v1.

71.

Yang

Tang

. Interaction of anxiety and hypertension on quality of life among patients with gynecological cancer: a cross-sectional study. BMC Psychiatr. 2023;23(1):26. doi:10.1186/s12888-023-04521-5.

72.

Snarska

Chorąży

Szczepański

Wojewódzka-Żelezniakowicz

Ładny

. Quality of life of patients with arterial hypertension. Medicina (Kaunas). 2020;56(9):459. doi:10.3390/medicina56090459.

73.

Tous-Espelosín

Gorostegi-Anduaga

Corres

MartinezAguirre-Betolaza

Maldonado-Martín

. Impact on health-related quality of life after different aerobic exercise programs in physically inactive adults with overweight/obesity and primary hypertension: data from the EXERDIET-HTA study. Int J Environ Res Public Health. 2020;17(24):9349. doi:10.3390/ijerph17249349.

74.

Burgoyne

. Reducing economic burden and improving quality of life in pulmonary arterial hypertension. Am J Manag Care. 2021;27(3 Suppl):S53-s58. doi:10.37765/ajmc.2021.88611.

75.

Zhang

Huang

Zhang

. The effect of high blood pressure-health literacy, self-management behavior, self-efficacy and social support on the health-related quality of life of Kazakh hypertension patients in a low-income rural area of China: a structural equation model. BMC Publ Health. 2021;21(1):1114. doi:10.1186/s12889-021-11129-5.

76.

Prevolnik Rupel

Mori Lukančič

Ogorevc

. Costs and quality of life in patients with systemic arterial hypertension in Slovenia. Value Health Reg Issues. 2023;33:49-55. doi:10.1016/j.vhri.2022.09.001.

77.

Tang

Wang

Zhang

, et al. Associations between diabetes and quality of life among breast cancer survivors. PLoS One. 2016;11(6):e0157791. doi:10.1371/journal.pone.0157791.

78.

Petek

Petek-Ster

Tusek-Bunc

. Health behavior and health-related quality of life in patients with a high risk of cardiovascular disease. Zdr Varst. 2018;57(1):39-46. doi:10.2478/sjph-2018-0006.

79.

Rossi

Bosinelli

Di Stefano

Picchi

Noberasco

Baccetti

. Implementing an integrative oncology paradigm in cancer care: the tuscan regional healthcare system. J Integr Complement Med. 2022;28(12):965-968. doi:10.1089/jicm.2022.0522.

80.

Perry

Hoerger

Seibert

Gerhart

O'Mahony

Duberstein

. Financial strain and physical and emotional quality of life in breast cancer. J Pain Symptom Manage. 2019;58(3):454-459. doi:10.1016/j.jpainsymman.2019.05.011.

81.

Roope

LSJ

. First estimates of inequality benchmark incomes for a range of countries. PLoS One. 2021;16(3):e0248178. doi:10.1371/journal.pone.0248178.

82.

McFarland

Hill

Montez

. Income inequality and population health: examining the role of social policy. J Health Soc Behav. 2023;64(1):2-20. doi:10.1177/00221465221109202.

83.

Singh

Katoch

Pal

Negi

. Quality of life outcomes and determining factors in breast cancer patients reporting to a tertiary care centre in the sub-himalayan region of India. Cureus. 2024;16(2):e55112. doi:10.7759/cureus.55112.

84.

Islam

Atreya

Nepal

, et al. Assessment of quality of life (QOL) in cancer patients attending oncology unit of a Teaching Hospital in Bangladesh. Cancer Rep (Hoboken). 2023;6(8):e1829. doi:10.1002/cnr2.1829.

85.

Khatiwoda

Dhungana

Sapkota

Singh

. Health-related quality of life of patients receiving cancer treatment in Nepal: a hospital-based cross-sectional study. J Nepal Health Res Counc. 2021;19(1):26-31. doi:10.33314/jnhrc.v19i1.3052.

Understanding the Quality of Life Among Patients With Cancer in Saudi Arabia: Insights From a Cross-Sectional Study

Abstract

Introduction

Methods

Results

Conclusion

Keywords

Introduction

Methods

Design and Setting

Inclusion and Exclusion Criteria

Sampling approach and sample size calculations

Patient Identification

Survey contents

Statistical Analysis

Results

Baseline Characteristics of Cancer Patients

Factors Affecting QoL in Cancer Patients

Discussion

Conclusion

Footnotes

Acknowledgement

Declaration of Conflicting Interests

Funding

Ethical Statement

ORCID iDs

References