Study design and participants
This cross-sectional study was conducted at Universiti Malaya Medical Centre (UMMC), a quaternary hospital in Malaysia, and involved the consecutive invitation of patients with haematological cancers from the years 2014 to 2016. Inclusion criteria encompassed females aged 18 years old and above, engaged in an intimate relationship, with confirmed haematological malignancy, and either on active treatment or having completed treatments. Exclusion criteria comprised those who were pregnant at the time of the interview, had undergone previous major gynaecological surgery or pelvic irradiation, had a history of other malignancies, or had a psychiatric illness. The study received approval from the Medical Ethics Committee at UMMC (Reference Number: 1024.3) and adhered to the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants.
Procedures
Demographic data including current age, ethnicity, marital status, education level, comorbidity, menopausal status, type of haematological malignancy, age at treatment initiation, types of active treatment received, and the status of treatment were obtained through patients interview and examination of the medical records. Participants underwent assessments using the Female Sexual Function Index (FSFI), the Hospital Anxiety and Depression Scale (HADS) and the European Organization for Research and Treatment of Cancer QLQ-C30 (EORTC QLQ-C30) version 3.0 questionnaire. Patients were instructed to respond to the questionnaires in English, Malay, or Chinese independently, based on their language preferences (17–22). In cases of uncertainty, participants were encouraged to seek clarification from the investigators. All assessment were completed independently by participants on the same day as the interview.
Operational definition
Haematological cancers were grouped into four types: ‘lymphoma’, ‘’acute leukaemia, ‘chronic leukaemia’, and ‘myeloma and others’. A patient is considered to have achieved menopausal status when they have experienced absence of menstruation for at least one year (23). Active treatment modalities for haematological cancer patients include chemotherapy, the combination of chemotherapy and radiotherapy, and the combination of chemotherapy with haemopoietic stem cell transplantation (HSCT). Immunotherapy may be added to each of these treatment regimens. Patients are considered to have completed treatment if they have received all courses of treatment regimens in accordance with National Comprehensive Cancer Network® or European Society for Medical Oncology guidelines. Otherwise, they are still in active treatment.
Research tools
1. Female sexual function
FSFI is a validated self-reported multidimensional questionnaire that has been demonstrated to adequately measure sexual function in female cancer patients (24). Consisting of 19 items, it assesses 6 domains: desire, arousal, lubrication, orgasm, satisfaction, and pain. Each domain has the highest score of six, with a higher score indicating better sexual function. The FSFI exhibits excellent reliability for both the total score (Cronbach's α coefficient, 0.97) and subscales (Cronbach's α coefficient, 0.89–0.96) (24). In this study, a total score of less than 26.55 to identify SD (25).
2. Psychological assessment
To assess the psychological distress of the patients, we used the HADS. The HADS consists of 14 items, divided into two subscales: anxiety (HADS-A) with 7 items and depression (HADS- D) with 7 items, each rated on a point scale. Both the anxiety and depression subscales have a maximum score of 21. Scores ranging from 0 to 7 on either subscale are considered “normal”, while scores of 8 and above indicate the presence of psychological stress (26). The HADS-A demonstrates a Cronbach's α coefficient ranging from 0.69 to 0.93 (mean 0.83) and the HADS-D has Cronbach’s α coefficient ranging from 0.67 to 0.90 (mean 0.82) (27).
3. Health-related Quality of Life
HRQoL was assessed using the EORTC QLQ-C30 version 3.0 (28, 29). It consists of 30 questions that encompass multi-item scales such as the Global Health Status/ QoL (QL2), 5 functional scales (physical functioning [PF2], role functioning [RF2], emotional functioning [EF], cognitive functioning [CF], and social functioning [SF]), 3 symptoms scale and 6 single-items. The symptom scales or items include fatigue [FA], nausea and vomiting [NV], pain [PA], dyspnoea [DY], insomnia [SL], appetite loss [AP], constipation [CO], diarrhoea [DI], and financial difficulties [FI].
Responses to each item were scored on a scale of 1. ‘Not at all’, 2. ‘A little’, 3. ‘Quite a bit’, and 4. ‘Very much’ except for QL2, which ranges from 1. ‘Very poor’ to 7. ‘Excellent’. A linear transformation to a ‘0–100’ scale for the score of the items was carried out according to the EORTC QLQ-C30 Scoring Manual (30). High scores on the global and functional scales indicate good QoL, while low scores on symptom scales represent a less intense symptom experience. The EORTC QLQ-C30 version 3.0 has good reliability with Cronbach’s α coefficient consistently exceeding 0.70 in most of its multi-item scales (28).
Data Analysis
Statistical analysis was conducted using IBM Statistical Package for Social Science Version 27. A descriptive analysis was done to describe the characteristics of the participants, in which continuous data were presented in means and standard deviations or median with interquartile range (IQR), while categorical data were presented in numbers and percentages in parentheses. The difference between SD and non-SD group were analysed using Chi-square test or Fisher’s Exact test for categorical data, and Mann-Whitney test for continuous non-parametric data. Parameters with p < 0.05 and factors deemed significant in other studies such as current age (31–33), marital status (32, 33), education(31–33), diagnosis (31, 33), age at treatment (33) were included as covariates in the binary logistic regression. The results are presented in odds ratio (OR) with a 95% confidence interval (CI). The correlation between SD and QoL was assessed using the Spearman test, followed by linear regression test. Effect size was interpreted based on the Spearman correlation coefficient, where values of 0.1–0.3 indicating a small effect, 0.3–0.5 a medium effect and greater than 0.5 a large effect (34). All statistical tests were two-tailed with an alpha value of 0.05, where a p-value less than 0.05 is considered statistically significant.