Unmet supportive care needs in patients with advanced cancer and its impact on distress

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Miranda, Benjamin L. Musher, Hoda J. Badr This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5875245/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Apr, 2025 Read the published version in BMC Palliative Care → Version 1 posted 16 You are reading this latest preprint version Abstract Purpose Patients with advanced cancer endure considerable physical and emotional distress without sufficient supportive care. In order to identify areas for intervention, this cross-sectional study examined the relationship between cancer-related symptoms, supportive care needs, and distress levels in patients with advanced lung, head and neck, or gastrointestinal cancers. Methods Baseline data from 158 patients enrolled in a multisite dyadic interventional study were analyzed using the M.D. Anderson Symptom Inventory (MDASI) and Supportive Care Needs Survey (SCNS-34). Pearson correlations and multiple regression analyses were used to explore associations between supportive care needs and distress. Results Distress levels were moderate across the study population, with fatigue, pain, and disturbed sleep being the most reported symptoms. Patients who lived with their caregivers reported significantly lower needs in four out of five domains. Positive correlations were found between distress levels and supportive care needs in the psychological (p < 0.001), health system (p = 0.001), patient care and support (p = 0.003), and physical and daily living domains (p < 0.001). Multiple regression analysis showed that these domains collectively explained a significant portion of the variance in distress levels (R2 = 0.169, p < 0.001). Conclusion Independent of demographic or clinic characteristics, patients with advanced cancer experience significant distress and unmet supportive care needs, particularly in psychological and health system domains. The association between living with caregivers and lower reported needs suggests that caregiver support may play a crucial role in meeting these needs. Therefore, integrating strategies that involve and support caregivers could potentially reduce distress and improve the quality of life for patients with advanced cancer. advanced cancer caregiver distress supportive care Figures Figure 1 Introduction While cancer mortality rates have steadily improved over the past four decades, the global burden of cancer is expected to increase to 29.9 million new cases per year by 2040 (NCI). Despite advances in cancer therapy, patients still have significant unmet supportive care needs at the time of diagnosis and throughout treatment. As patients are diagnosed earlier and living longer with cancer, there has been growing awareness of the considerable psychosocial, financial, and supportive care needs that impact a patient’s overall quality of life and level of distress. Emotional distress is common, yet often overlooked, and negatively impacts quality of life in patients with cancer [ 1 , 2 ]. Approximately one-third of oncology patients experience high levels of psychological distress [ 3 , 4 ]. The National Cancer Institute defines distress as “emotional, social, spiritual, or physical pain or suffering” that may impact a patient’s mood and interfere with their ability to manage normal activities. Psychological distress has been associated with cancer mortality [ 5 ]. In order to identify patients who may need referrals to psychologists, chaplains, or social workers, the National Comprehensive Cancer Network (NCCN) recommends screening all cancer patients for distress using validated tools such as the Distress Thermometer [ 6 ]. In reality, many patients do not receive distress screening at diagnosis, and those who do often face other barriers to intervention, especially if they are uninsured or live in a rural or resource-poor region. High levels of emotional distress have been associated with physical symptoms such as pain and fatigue [ 7 ]. In patients with lung cancer, emotional distress has also been associated with dysfunctional family relationships, problems with emotional functioning, and lack of information about diagnosis and treatment [ 7 ]. Palliative care, which focuses on decreasing pain and suffering in patients with advanced or complex illness, has been proposed as a potentially effective intervention for patients experiencing high levels of distress. Consultation with a palliative care specialist has been associated with improved symptom control, enhanced patient understanding of their diagnosis and prognosis, decreased utilization of health care resources, and high satisfaction among patients and their families. In patients with metastatic lung cancer, early palliative care referral has yielded improved quality of life and mood [ 8 ]. However, routine palliative care visits do not typically address complex psychosocial needs such as self-esteem, communication, caregiver distress, and social functioning. Furthermore, existing research often lacks a comprehensive approach, focusing on either psychological distress or supportive care needs but rarely examining the correlation between the two in advanced cancer patients. Many studies do not account for demographic and clinical characteristics that may influence these factors [ 9 ]. This narrow focus limits the development of holistic interventions that address the multifaceted needs of this patient population. Patients living with advanced cancer and their caregivers critically need effective, patient-centered interventions that reduce distress and enhance quality of life. However, multiple barriers to providing more family-centered care exist, including restricted provider time and availability, a lack of provider training in psychosocial interventions, and limited insurance reimbursement. Approximately one-third of patients with cancer experience mental illnesses such as depression, anxiety, or adjustment disorders, the majority of whom are not treated [ 10 , 11 ], and those with advanced disease have higher intensity care needs, more severe and debilitating symptoms, increased financial burden, and higher rates of hospitalization and readmission [ 12 ]. The psychosocial impact of cancer also has ripple effects on patients’ families and healthcare systems. For example, caregivers of cancer patients are more likely to stop working and take on increased household debt compared with non-cancer caregivers [ 13 ]. While previous studies have explored distress and supportive care needs in cancer patients, few have specifically focused on patients with advanced lung, head and neck, or gastrointestinal cancers at the time of treatment initiation. Moreover, the interplay between caregiver involvement, specific supportive care needs, cancer-related symptoms, and distress levels remain underexplored. This study uniquely addresses these gaps by evaluating these factors concurrently, with the hope of providing a more nuanced understanding of distress in advanced cancer patients, ultimately guiding the development of more targeted and effective supportive care interventions. Methods Study and Sample Eligibility criteria for this cross-sectional study included being an adult (age 18 or over) with advanced lung (at least stage 3A), head and neck (H&N, stage 4B or 4C), or gastrointestinal (GI, stage 4) cancer within one month of treatment initiation, having an Eastern Cooperative Oncology Group (ECOG) performance status of 0–2, having a primary caregiver who was at least 18 years old, having the ability to read and understand English at a 6th grade level, and having the capacity to provide informed consent. Patients were excluded if they had diminished mental capacity, had significant hearing impairment that prevented telephone use, were pregnant, or were currently enrolled in hospice. Procedure The current study, which was part of a larger multisite dyadic intervention designed to improve self-management and coordination of care for patients with advanced cancer and their caregivers, used baseline survey data collected at the time of treatment initiation to assess subjects’ cancer-related symptoms, supportive care needs, and distress levels. The clinical trial was conducted between 2015 and 2021 after approval by Baylor College of Medicine’s Institutional Review Board (H-39002). All procedures adhered to ethical guidelines for research involving human subjects in accordance with the 1964 Declaration of Helsinki and its later amendments, and written informed consent was obtained from all participants prior to enrollment. Eligible patients were identified by research assistants who reviewed clinic schedules and electronic medical records in the outpatient oncology clinics. After obtaining permission from the treating physicians, patients were approached during their clinic visits to discuss potential participation. In cases where in-person recruitment was not feasible, patients were contacted by telephone. Consented patients were provided with a baseline questionnaire, which they could complete while waiting for their clinic appointment or complete at home and return to the research team in person or by mail. To provide flexibility in data collection methods, patients also had the option to complete the survey by telephone or online. Demographics and clinical characteristics questionnaire Items in the baseline questionnaire included gender, race, ethnicity, age, employment status, annual pre-tax household income, level of education, marital status, and caregiver type (i.e. relationship of the primary caregiver to the patient). Medical history was also obtained, encompassing comorbidities, prior mental health diagnoses, medications, and prior attendance in counseling/support groups. Health literacy was assessed using the Single Item Literacy Screener (SILS) [ 14 ], which asks patients how often they need help reading hospital materials. Responses range from 1 (“Never”) to 5 (“Always”) with a score of 3 or higher indicating limited health literacy. Additional clinical data such as tumor type and stage were obtained from the patient’s electronic medical record. M.D. Anderson Symptom Inventory The M.D. Anderson Symptom Inventory (MDASI), [ 15 ] includes 13 core items to evaluate symptom severity independent of cancer type: pain, fatigue, disturbed sleep, distress (emotional), shortness of breath, drowsiness, dry mouth, sadness, difficulty remembering, numbness or tingling, lack of appetite, nausea, and vomiting. Each symptom is rated on a 0 to 10 numeric scale, with 0 indicating “not present” and 10 indicating “as bad as you can imagine.” Higher scores reflect greater symptom severity. For patients with GI cancers, 5 additional items included constipation, diarrhea, dysphagia, taste changes, and bloating. For patients with H&N malignancies, 9 additional items were included: mucus production, dysphagia, coughing/choking, dysphonia, skin pain/burning/rash, constipation, taste changes, mouth/throat sores, and teeth/gum problems. For patients with lung cancer, 3 additional items were included: cough, constipation, and sore throat. The MDASI also assesses how much symptoms interfere with six daily functions: relations with others, enjoyment of life, mood, walking, general activity, and working. Each item is rated on a 0 to 10 numeric scale, with responses ranging from 0 (“Did not interfere”) to 10 (“Interfered completely”). The mean score of these six symptom interference items was used as a measure of overall distress. Cronbach alpha was 0.90 indicating excellent reliability. Supportive Care Needs Survey The Supportive Care Needs Survey (SCNS-34) uses 34 items to measure unmet needs across five key domains: psychological, health system and information, physical and daily living, patient care and support, and sexuality [ 16 ]. Responses are rated on a 5-point Likert scale ranging from 1 (“No need”) to 5 (“High need”). Scores were summed for each domain and then standardized to a range from 0 to 100 [ 17 ]. Cronbach alphas for each of the subscales and ranged from 0.86 to 0.93, indicating high internal consistency. Statistical Analyses All statistical analyses were conducted using SPSS version 29.0 software (IBM Corp., Armonk, NY, USA). Descriptive statistics- including means, standard deviations, and frequencies- were calculated to summarize demographic and clinical characteristics of the sample. To compare mean differences in distress levels and supportive care needs across different demographic and clinical groups, Student's t-tests were used for comparisons between two groups, and one-way analysis of variance (ANOVA) was applied for comparisons across multiple groups. Pearson correlation coefficients were calculated to evaluate the relationships between supportive care needs (as measured by the SCNS-34 domains) and distress levels (as measured by the MDASI Core Severity Index). Multiple regression analyses were conducted to determine the predictive value of supportive care needs domains on distress levels, adjusting for potential confounders. All statistical tests were two-sided, and a p-value of < 0.05 was considered statistically significant. Results Patient Demographics and Clinical Characteristics A total of 158 patients completed the baseline surveys. Demographic and clinical characteristics are detailed in Table 1. The mean age of participants was 61 years, ranging from 35 to 91 years. The majority of participants were male (62%). Regarding race, 71% identified as White, 25% as Black or African American, 2.5% as Asian, and 0.6% as Multiracial. In terms of ethnicity, 16.5% identified as Hispanic or Latino. Limited health literacy was reported by 15.2% of patients. Tumor types included GI (36.7%), lung (38.0%), and H&N cancers (25.3%), with most patients diagnosed at stage IV (84.2%). Caregivers were primarily spouses/partners (67.1%) or adult daughters (17.7%), and 78.5% of patients lived with their caregiver. Table 1: Distress Levels Among Patients with Various Demographic and Clinical Characteristics Demographic Frequency (%) MDASI Symptom Interference a Mean ± SD t/F/ Pearson Coefficient p Total Patients 158 (100%) 3.2 ±1.8 N/A N/A Gender Male Female 98 (62%) 60 (38%) 3.3 ± 1.9 3.0 ± 1.8 1.039 0.301 Age 60 8 (5.1%) 72 (45.6%) 78 (49.4%) 2.4 ± 1.8 3.4 ± 1.9 3.1 ± 1.8 -0.36 0.650 Caregiver Type Spouse/Partner Adult Daughter Adult Son Sibling/Sister Daughter in Law Mother Friend/Neighbor Ex-spouse 106 (67.1%) 28 (17.7%) 1 (0.6%) 8 (5.1%) 1 (0.6%) 3 (1.9%) 7 (4.4%) 4 (2.5%) 3.2 ± 1.9 3.5 ± 1.4 4.8 3.5 ± 1.9 3.8 1.7 ± 1.4 1.8 ± 1.3 4.8 ± 2.8 1.588 0.143 Marriage Status Single Married Cohabiting Divorced/Separated Widowed 18 (11.4%) 94 (59.5%) 15 (9.5%) 24 (15.2%) 7 (4.4%) 2.7 ± 1.7 3.1 ± 1.9 3.1 ± 1.6 4.0 ± 1.8 3.7 ± 2.0 1.843 0.123 Race White Black Asian Multiracial 113 (71.5%) 40 (25.3%) 4 (2.5%) 1 (0.6%) 3.2 ± 1.8 3.3 ± 2.0 3.3 ± 2.5 0.3 0.908 0.439 Education Did not complete HS HS diploma or GED Technical/Vocational Some College BS/BA MS/MA/MPH MD/PHD/JD 12 (7.6%) 31 (19.6%) 10 (6.3%) 42 (26.6%) 41 (25.9%) 8 (5.1%) 13 (8.2%) 3.1 ± 1.5 3.2 ± 1.9 3.7 ± 1.4 3.2 ± 2.0 3.1 ± 1.8 3.6 ± 2.5 2.9 ± 1.9 0.274 0.949 Employment Status Full time Part time Unemployed Retired Housewife 53 (33.5%) 10 (6.3%) 36 (22.8%) 46 (29.1%) 10 (6.3%) 2.8 ± 1.8 3.3 ± 2.2 3.6 ± 1.7 3.2 ± 2.0 3.5 ±1.5 1.015 0.402 Household Annual Income $150,001 36 (22.8%) 51 (32.3%) 21 (13.3%) 12 (7.6%) 3.4 ± 2.0 3.1 ± 1.6 3.3 ± 2.2 3.6 ± 1.8 0.063 0.491 Cancer Type GI Lung H&N 58 (36.7%) 60 (38.0%) 40 (25.3%) 3.1 ± 1.7 3.2 ± 2.0 3.4 ± 1.9 0.312 0.732 Caregiver Lives w/ Patient Yes No 124 (78.5%) 34 (21.5%) 3.2 ± 1.6 3.2 ± 1.9 -0.149 0.281 History of Psych Dx Yes No 20 (12.7%) 130 (82.3%) 3.6 ± 1.8 3.1 ± 1.9 -1.042 0.443 a Distress was measured using the MDASI Symptom Interference Score, which is the mean score of six items asking patients how much their symptoms interfere with daily functions Distress Levels Associated with Cancer-Related Symptoms The MDASI was utilized to assess distress related to cancer symptoms. The three highest scoring symptoms were fatigue (mean score 4.78), pain (mean score 4.13), and disturbed sleep (mean score 3.91) (Table 2). Symptom severity varied by tumor type (Figure 1): patients with H&N cancer reported more dry mouth (p=0.012), while those with lung cancer reported more shortness of breath (p <0.001). The mean MDASI symptom interference score, a composite measure of distress, was 3.20, indicating moderate distress overall. However, no statistically significant differences in distress were observed across gender, race, age, cancer type, caregiver type, marital status, education level, health literacy, employment status, income, or psychiatric diagnosis (Table 1). Table 2: Top 5 Most Severe MDASI Core Symptoms MDASI Core Item Mean Score a 1 Your fatigue at its worst 4.8 2 Your pain at its worst 4.1 3 Your disturbed sleep at its worst 3.9 4 Your problem with lack of appetite at its worst 3.8 5 Your feeling of being distressed at its worst 3.7 a Patients reported symptom severity on a scale from 0 (“not present”) to 10 (“as bad as you can imagine”). Supportive Care Needs and Their Variation Among Patients The baseline SCNS-34 was performed at time of study enrollment to evaluate unmet supportive care needs. The psychological domain had the highest reported needs (mean score 38.20), followed by the health system domain (mean score 35.30) (Table 3). No significant variations in SCNS domain scores were found based on gender, age, race, cancer type, marital status, education level, health literacy, employment status, income, and psychiatric diagnosis history. However, patients who lived with their caregiver reported significantly lower needs in the psychological (p=0.039), patient care and support (p=0.005), physical and daily living (p <0.001), and sexuality domains (p=0.018) compared to those without a live-in caregiver. There was a significant difference in the physical and daily living domain based on caregiver type, with the highest mean score in a patient with an adult son caregiver (n=1); however, conclusions are limited by the small sample size. Table 3: Supportive Care Domains Ranked by Highest Need SCNS-34 Domains Mean Score a 1 Psychological 38.2 2 Health System 35.3 3 Physical and Daily Living 21.5 4 Patient Care and Support 14.1 5 Sexuality 9.2 a Responses are rated on a 5-point Likert scale ranging from 1 (“No need”) to 5 (“High need”). Scores were summed for each domain and then standardized to a range from 0 to 100 [17]. Associations Between Supportive Care Needs and Distress Levels To explore the associations between supportive care needs and distress levels, Pearson correlation coefficients were calculated for each SNCS domain using the mean MDASI Symptom Interference. Significant correlations were observed between distress and several domains: psychological (r=0 .342, p <0.001), health system (r=0.253, p=0.001), patient care and support (r=0.237, p=0.003), and physical living and daily living (r=0.378, p <0.001). A trend toward significance was noted for the sexuality domain (r=0.142, p=0.075). Multiple regression analysis was conducted to further assess the relationship between supportive care needs domains and distress, considering all five SCNS domains together. The analysis showed that the combined domains significantly explained variance in distress levels (R2=0.169, p <0.001) (Table 4). Table 4: Multiple Regression Analysis of Supportive Care Domains as a Predictor of Distress SCNS Domain B SE β t p Psychological 0.020 0.010 0.235 1.967 0.051 Health System 0.004 0.011 0.047 0.357 0.721 Patient Care and Support -0.005 0.023 -0.029 -0.219 0.827 Physical and Daily Living 0.041 0.015 0.265 2.705 0.008 Sexuality -0.026 0.022 -0.114 -1.192 0.235 R2 = 0.169 B: regression coefficient SE: standard error of the regression coefficient β: standardized regression coefficient Discussion This study analyzed the relationship between cancer-related symptoms, supportive care needs, and distress levels among patients with advanced lung, H&N, or GI cancers at the time of treatment initiation. Additionally, it investigated how specific supportive care needs correlate with distress levels and whether demographic or clinical characteristics influence these associations. Our findings contribute to the growing body of literature on the psychosocial needs of patients with advanced cancer and highlight important areas for targeted interventions. The results indicate that distress levels, as measured by the MDASI Core Severity Index, were moderate across the sample, with fatigue, pain, and disturbed sleep being the most prevalent patient-reported symptoms. These findings are consistent with prior research indicating that physical symptoms significantly contribute to distress in cancer patients, particularly those with advanced disease stages [ 18 ]. Interestingly, while symptom distress varied by cancer type—with head and neck cancer patients reporting more dry mouth and lung cancer patients more shortness of breath—there were no statistically significant differences in overall distress levels based on demographic or clinical characteristics. These findings suggest that the emotional burden of advanced cancer is a pervasive experience, transcending factors such as age, gender, race, and cancer type. This universality may reflect the profound impact of an advanced cancer diagnosis on patients’ psychological well-being, regardless of individual characteristics. It underscores the need for universal screening and interventions for distress in this population. When considering which patients may need the greatest intervention, our analysis suggests that those with higher psychological and health system needs—the domains with the highest reported scores—might benefit most from targeted supportive care interventions. Patients living without a caregiver reported higher needs in these domains, possibly attributed to the lack of immediate emotional and practical support. Caregivers often assist with symptom management, provide psychological comfort, and help navigate the healthcare system. Without this support, patients may feel overwhelmed, leading to increased distress and unmet needs. These findings highlight the critical role caregivers play in the well-being of patients with advanced cancer. Thus, interventions should prioritize psychological support and healthcare system navigation assistance for these patients who might lack the emotional and practical support provided by a caregiver. These findings are particularly relevant in light of the recent enactment of the CARE (Caregiver Advise, Record, and Enable) Act in many states across the U.S., which mandates that hospitals identify a designated caregiver upon a patient's discharge and provide the necessary training and information to support at-home care [ 19 ]. Lee et al. found that patients hospitalized in states that had adopted the CARE act reported improved communication with nurses/physicians and more consistent receipt of discharge information when compared to patients in non-CARE states [ 19 ]. Our results suggest that complying with this legislation could have additional benefits beyond legal adherence, especially for chronically ill patients with high symptom burden. By involving caregivers in discharge planning and ensuring they are equipped to support patients, hospitals may effectively reduce patient distress and unmet supportive care needs post-discharge. These results highlight a significant opportunity for healthcare providers to enhance patient outcomes through structured engagement with and education of caregivers. The associations between supportive care needs and distress levels were further elucidated through Pearson correlation and regression analyses. Significant correlations were found between distress and several supportive care needs domains, including psychological, health system, patient care and support, and physical and daily living. These findings underscore the interconnectedness of psychological distress and supportive care needs, suggesting that unmet needs in these areas likely contribute to higher distress levels among patients. Thus, patients reporting high needs in these domains—particularly psychological and health system needs—are those who may require the greatest intervention to manage distress effectively. The strengths of this study include its use of validated instruments to assess both symptom burden and supportive care needs and its inclusion of a diverse population of patients across multiple cancer types, thus enhancing the generalizability of its findings. However, there are limitations to consider. The cross-sectional design limits our ability to establish causality or directionality in the relationships between distress and supportive care needs. Furthermore, the reliance on self-reported data may introduce response bias, particularly concerning sensitive topics such as psychological distress and sexual health. Additionally, the exclusion of non-English-speaking patients may limit generalizability to more diverse populations. Clinically, these findings highlight the importance of integrated care approaches that prioritize both symptom management and supportive care tailored to individual patient needs. Given the benefits of caregiver involvement, healthcare systems should prioritize strategies to engage and educate caregivers effectively, particularly at discharge, to reduce patient distress and unmet needs. Future research should consider longitudinal designs to explore causal pathways between distress and supportive care needs over time, as well as the impact of specific interventions on both symptom burden and perceived supportive care needs. Additionally, exploring the impact of policies like the CARE Act on patient outcomes could provide valuable insights into optimizing care for patients with advanced cancer. In conclusion, this study underscores the significant psychosocial and supportive care needs of patients with advanced cancer. Patients with higher psychological and health system needs, especially those lacking caregiver support, may require the greatest intervention to manage their distress effectively. Addressing these needs through comprehensive, patient-centered care may help mitigate distress and improve quality of life, ultimately enhancing outcomes for both patients and their caregivers. Declarations Ethics approval and consent to participate: This study was approved by the Institutional Review Board at Baylor College of Medicine (H-39002) and conducted in accordance with the 1964 Declaration of Helsinki and its later amendments. Informed consent was obtained from all individual participants included in the study. Consent for publication : Not applicable Availability of data and materials : Contact the corresponding author for data requests. Competing interests: Kayla Miranda, Benjamin Musher, and Hoda Badr declare that they have no competing interests. Funding: This study was funded by the American Cancer Society (RSG 15-058-01 PCSM; PI: Badr). The funders had no role in study design, data collection, analysis, and interpretation, or preparation of the manuscript. Authors’ contributions: All authors contributed to the study conception and design. Material preparation and data collection were performed by Hoda Badr. Data analysis was performed by Kayla Miranda. All authors contributed to drafting the manuscript. All authors read and approved the final manuscript. 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Cite Share Download PDF Status: Published Journal Publication published 21 Apr, 2025 Read the published version in BMC Palliative Care → Version 1 posted Editorial decision: Revision requested 05 Mar, 2025 Reviews received at journal 19 Feb, 2025 Reviews received at journal 13 Feb, 2025 Reviews received at journal 13 Feb, 2025 Reviewers agreed at journal 13 Feb, 2025 Reviews received at journal 12 Feb, 2025 Reviewers agreed at journal 07 Feb, 2025 Reviewers agreed at journal 07 Feb, 2025 Reviews received at journal 07 Feb, 2025 Reviewers agreed at journal 07 Feb, 2025 Reviewers agreed at journal 07 Feb, 2025 Reviewers invited by journal 07 Feb, 2025 Editor invited by journal 29 Jan, 2025 Editor assigned by journal 27 Jan, 2025 Submission checks completed at journal 27 Jan, 2025 First submitted to journal 21 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Miranda","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYBACCQYGxgNAmgfCqTgAE8WrhQFJyxkStEA4jG1EaJFsP2Nw4AfDNhnz9rMHb/ycd0det4H54G0ePFqkeXIMDvYw3OaROZOXbNm77ZnhtgNsydb4tMgx5Bgc4AFqkWDIMZPg3XY4wewAj5k0Xi38bwwO/gFp4X9jJvl3DkgL/ze8WqQlcgwOg22RyDGT5m0A28KGV4vkjGcFh2UMQFreGFvLHAP65TCbseUcPFokzidvfPim4ra9BH+O4c03NXfkzY43P7zxBo8WBgYOAwYGA2QBZrzKQYD9AUElo2AUjIJRMMIBAMWJTLQYmsYIAAAAAElFTkSuQmCC","orcid":"","institution":"Baylor College of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Kayla","middleName":"W.","lastName":"Miranda","suffix":""},{"id":407681884,"identity":"aa810caf-6b00-41b3-8894-3c23955c4b22","order_by":1,"name":"Benjamin L. Musher","email":"","orcid":"","institution":"Baylor College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"L.","lastName":"Musher","suffix":""},{"id":407681886,"identity":"cab04603-bbac-4617-9a8e-e2ccaa4082c6","order_by":2,"name":"Hoda J. Badr","email":"","orcid":"","institution":"Baylor College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hoda","middleName":"J.","lastName":"Badr","suffix":""}],"badges":[],"createdAt":"2025-01-21 17:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5875245/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5875245/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12904-025-01746-x","type":"published","date":"2025-04-21T15:57:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":75312618,"identity":"2cc0f4b4-d08f-4704-9328-0aa3fe4846bb","added_by":"auto","created_at":"2025-02-03 09:15:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105795,"visible":true,"origin":"","legend":"\u003cp\u003eMDASI Core Symptom Severity by Cancer Type\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5875245/v1/3fa9211933c2909825d4c819.png"},{"id":81569721,"identity":"f5988f08-a94d-4f47-a439-760119071773","added_by":"auto","created_at":"2025-04-28 16:10:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":707911,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5875245/v1/69f5644c-e951-4f23-aee7-efb278fd85f1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unmet supportive care needs in patients with advanced cancer and its impact on distress","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWhile cancer mortality rates have steadily improved over the past four decades, the global burden of cancer is expected to increase to 29.9\u0026nbsp;million new cases per year by 2040 (NCI). Despite advances in cancer therapy, patients still have significant unmet supportive care needs at the time of diagnosis and throughout treatment. As patients are diagnosed earlier and living longer with cancer, there has been growing awareness of the considerable psychosocial, financial, and supportive care needs that impact a patient\u0026rsquo;s overall quality of life and level of distress.\u003c/p\u003e \u003cp\u003eEmotional distress is common, yet often overlooked, and negatively impacts quality of life in patients with cancer [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Approximately one-third of oncology patients experience high levels of psychological distress [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The National Cancer Institute defines \u003cem\u003edistress\u003c/em\u003e as \u0026ldquo;emotional, social, spiritual, or physical pain or suffering\u0026rdquo; that may impact a patient\u0026rsquo;s mood and interfere with their ability to manage normal activities. Psychological distress has been associated with cancer mortality [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In order to identify patients who may need referrals to psychologists, chaplains, or social workers, the National Comprehensive Cancer Network (NCCN) recommends screening all cancer patients for distress using validated tools such as the Distress Thermometer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In reality, many patients do not receive distress screening at diagnosis, and those who do often face other barriers to intervention, especially if they are uninsured or live in a rural or resource-poor region. High levels of emotional distress have been associated with physical symptoms such as pain and fatigue [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In patients with lung cancer, emotional distress has also been associated with dysfunctional family relationships, problems with emotional functioning, and lack of information about diagnosis and treatment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePalliative care, which focuses on decreasing pain and suffering in patients with advanced or complex illness, has been proposed as a potentially effective intervention for patients experiencing high levels of distress. Consultation with a palliative care specialist has been associated with improved symptom control, enhanced patient understanding of their diagnosis and prognosis, decreased utilization of health care resources, and high satisfaction among patients and their families. In patients with metastatic lung cancer, early palliative care referral has yielded improved quality of life and mood [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, routine palliative care visits do not typically address complex psychosocial needs such as self-esteem, communication, caregiver distress, and social functioning. Furthermore, existing research often lacks a comprehensive approach, focusing on either psychological distress or supportive care needs but rarely examining the correlation between the two in advanced cancer patients. Many studies do not account for demographic and clinical characteristics that may influence these factors [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This narrow focus limits the development of holistic interventions that address the multifaceted needs of this patient population.\u003c/p\u003e \u003cp\u003ePatients living with advanced cancer and their caregivers critically need effective, patient-centered interventions that reduce distress and enhance quality of life. However, multiple barriers to providing more family-centered care exist, including restricted provider time and availability, a lack of provider training in psychosocial interventions, and limited insurance reimbursement. Approximately one-third of patients with cancer experience mental illnesses such as depression, anxiety, or adjustment disorders, the majority of whom are not treated [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and those with advanced disease have higher intensity care needs, more severe and debilitating symptoms, increased financial burden, and higher rates of hospitalization and readmission [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The psychosocial impact of cancer also has ripple effects on patients\u0026rsquo; families and healthcare systems. For example, caregivers of cancer patients are more likely to stop working and take on increased household debt compared with non-cancer caregivers [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile previous studies have explored distress and supportive care needs in cancer patients, few have specifically focused on patients with advanced lung, head and neck, or gastrointestinal cancers at the time of treatment initiation. Moreover, the interplay between caregiver involvement, specific supportive care needs, cancer-related symptoms, and distress levels remain underexplored. This study uniquely addresses these gaps by evaluating these factors concurrently, with the hope of providing a more nuanced understanding of distress in advanced cancer patients, ultimately guiding the development of more targeted and effective supportive care interventions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy and Sample\u003c/h2\u003e \u003cp\u003eEligibility criteria for this cross-sectional study included being an adult (age 18 or over) with advanced lung (at least stage 3A), head and neck (H\u0026amp;N, stage 4B or 4C), or gastrointestinal (GI, stage 4) cancer within one month of treatment initiation, having an Eastern Cooperative Oncology Group (ECOG) performance status of 0\u0026ndash;2, having a primary caregiver who was at least 18 years old, having the ability to read and understand English at a 6th grade level, and having the capacity to provide informed consent. Patients were excluded if they had diminished mental capacity, had significant hearing impairment that prevented telephone use, were pregnant, or were currently enrolled in hospice.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eThe current study, which was part of a larger multisite dyadic intervention designed to improve self-management and coordination of care for patients with advanced cancer and their caregivers, used baseline survey data collected at the time of treatment initiation to assess subjects\u0026rsquo; cancer-related symptoms, supportive care needs, and distress levels.\u003c/p\u003e \u003cp\u003e The clinical trial was conducted between 2015 and 2021 after approval by Baylor College of Medicine\u0026rsquo;s Institutional Review Board (H-39002). All procedures adhered to ethical guidelines for research involving human subjects in accordance with the 1964 Declaration of Helsinki and its later amendments, and written informed consent was obtained from all participants prior to enrollment.\u003c/p\u003e \u003cp\u003eEligible patients were identified by research assistants who reviewed clinic schedules and electronic medical records in the outpatient oncology clinics. After obtaining permission from the treating physicians, patients were approached during their clinic visits to discuss potential participation. In cases where in-person recruitment was not feasible, patients were contacted by telephone.\u003c/p\u003e \u003cp\u003eConsented patients were provided with a baseline questionnaire, which they could complete while waiting for their clinic appointment or complete at home and return to the research team in person or by mail. To provide flexibility in data collection methods, patients also had the option to complete the survey by telephone or online.\u003c/p\u003e\n\u003ch3\u003eDemographics and clinical characteristics questionnaire\u003c/h3\u003e\n\u003cp\u003eItems in the baseline questionnaire included gender, race, ethnicity, age, employment status, annual pre-tax household income, level of education, marital status, and caregiver type (i.e. relationship of the primary caregiver to the patient). Medical history was also obtained, encompassing comorbidities, prior mental health diagnoses, medications, and prior attendance in counseling/support groups.\u003c/p\u003e \u003cp\u003eHealth literacy was assessed using the Single Item Literacy Screener (SILS) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], which asks patients how often they need help reading hospital materials. Responses range from 1 (\u0026ldquo;Never\u0026rdquo;) to 5 (\u0026ldquo;Always\u0026rdquo;) with a score of 3 or higher indicating limited health literacy. Additional clinical data such as tumor type and stage were obtained from the patient\u0026rsquo;s electronic medical record.\u003c/p\u003e\n\u003ch3\u003eM.D. Anderson Symptom Inventory\u003c/h3\u003e\n\u003cp\u003eThe M.D. Anderson Symptom Inventory (MDASI), [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] includes 13 core items to evaluate symptom severity independent of cancer type: pain, fatigue, disturbed sleep, distress (emotional), shortness of breath, drowsiness, dry mouth, sadness, difficulty remembering, numbness or tingling, lack of appetite, nausea, and vomiting. Each symptom is rated on a 0 to 10 numeric scale, with 0 indicating \u0026ldquo;not present\u0026rdquo; and 10 indicating \u0026ldquo;as bad as you can imagine.\u0026rdquo; Higher scores reflect greater symptom severity.\u003c/p\u003e \u003cp\u003eFor patients with GI cancers, 5 additional items included constipation, diarrhea, dysphagia, taste changes, and bloating. For patients with H\u0026amp;N malignancies, 9 additional items were included: mucus production, dysphagia, coughing/choking, dysphonia, skin pain/burning/rash, constipation, taste changes, mouth/throat sores, and teeth/gum problems. For patients with lung cancer, 3 additional items were included: cough, constipation, and sore throat. The MDASI also assesses how much symptoms interfere with six daily functions: relations with others, enjoyment of life, mood, walking, general activity, and working. Each item is rated on a 0 to 10 numeric scale, with responses ranging from 0 (\u0026ldquo;Did not interfere\u0026rdquo;) to 10 (\u0026ldquo;Interfered completely\u0026rdquo;). The mean score of these six symptom interference items was used as a measure of overall distress. Cronbach alpha was 0.90 indicating excellent reliability.\u003c/p\u003e\n\u003ch3\u003eSupportive Care Needs Survey\u003c/h3\u003e\n\u003cp\u003eThe Supportive Care Needs Survey (SCNS-34) uses 34 items to measure unmet needs across five key domains: psychological, health system and information, physical and daily living, patient care and support, and sexuality [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Responses are rated on a 5-point Likert scale ranging from 1 (\u0026ldquo;No need\u0026rdquo;) to 5 (\u0026ldquo;High need\u0026rdquo;). Scores were summed for each domain and then standardized to a range from 0 to 100 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Cronbach alphas for each of the subscales and ranged from 0.86 to 0.93, indicating high internal consistency.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analyses\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using SPSS version 29.0 software (IBM Corp., Armonk, NY, USA). Descriptive statistics- including means, standard deviations, and frequencies- were calculated to summarize demographic and clinical characteristics of the sample. To compare mean differences in distress levels and supportive care needs across different demographic and clinical groups, Student's t-tests were used for comparisons between two groups, and one-way analysis of variance (ANOVA) was applied for comparisons across multiple groups. Pearson correlation coefficients were calculated to evaluate the relationships between supportive care needs (as measured by the SCNS-34 domains) and distress levels (as measured by the MDASI Core Severity Index). Multiple regression analyses were conducted to determine the predictive value of supportive care needs domains on distress levels, adjusting for potential confounders. All statistical tests were two-sided, and a p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003ePatient Demographics and Clinical Characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 158 patients completed the baseline surveys. Demographic and clinical characteristics are detailed in Table 1. The mean age of participants was 61 years, ranging from 35 to 91 years. The majority of participants were male (62%). Regarding race, 71% identified as White, 25% as Black or African American, 2.5% as Asian, and 0.6% as Multiracial. In terms of ethnicity, 16.5% identified as Hispanic or Latino. Limited health literacy was reported by 15.2% of patients. Tumor types included GI (36.7%), lung (38.0%), and H\u0026amp;N cancers (25.3%), with most patients diagnosed at stage IV (84.2%). Caregivers were primarily spouses/partners (67.1%) or adult daughters (17.7%), and 78.5% of patients lived with their caregiver.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eDistress Levels Among Patients with Various Demographic and Clinical Characteristics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"460\" style=\"margin-right: calc(6%); width: 94%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 44.9008%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMDASI Symptom Interference\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et/F/\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003ePearson Coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eTotal Patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e158 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e3.2 \u0026plusmn;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Male\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e98 (62%)\u003c/p\u003e\n \u003cp\u003e60 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.3 \u0026plusmn; 1.9\u003c/p\u003e\n \u003cp\u003e3.0 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;45\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;45-60\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8 (5.1%)\u003c/p\u003e\n \u003cp\u003e72 (45.6%)\u003c/p\u003e\n \u003cp\u003e78 (49.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.4 \u0026plusmn; 1.8\u003c/p\u003e\n \u003cp\u003e3.4 \u0026plusmn; 1.9\u003c/p\u003e\n \u003cp\u003e3.1 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eCaregiver Type\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Spouse/Partner\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Adult Daughter\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Adult Son\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sibling/Sister\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Daughter in Law\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mother\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Friend/Neighbor\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ex-spouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e106 (67.1%)\u003c/p\u003e\n \u003cp\u003e28 (17.7%)\u003c/p\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003cp\u003e8 (5.1%)\u003c/p\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003cp\u003e3 (1.9%)\u003c/p\u003e\n \u003cp\u003e7 (4.4%)\u003c/p\u003e\n \u003cp\u003e4 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.2 \u0026plusmn; 1.9\u003c/p\u003e\n \u003cp\u003e3.5 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003cp\u003e3.5 \u0026plusmn; 1.9\u003c/p\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003cp\u003e1.7 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e1.8 \u0026plusmn; 1.3\u003c/p\u003e\n \u003cp\u003e4.8 \u0026plusmn; 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eMarriage Status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Single\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Married\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cohabiting\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Divorced/Separated\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (11.4%)\u003c/p\u003e\n \u003cp\u003e94 (59.5%)\u003c/p\u003e\n \u003cp\u003e15 (9.5%)\u003c/p\u003e\n \u003cp\u003e24 (15.2%)\u003c/p\u003e\n \u003cp\u003e7 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.7 \u0026plusmn; 1.7\u003c/p\u003e\n \u003cp\u003e3.1 \u0026plusmn; 1.9\u003c/p\u003e\n \u003cp\u003e3.1 \u0026plusmn; 1.6\u003c/p\u003e\n \u003cp\u003e4.0 \u0026plusmn; 1.8\u003c/p\u003e\n \u003cp\u003e3.7 \u0026plusmn; 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;White\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Black\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Asian\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Multiracial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e113 (71.5%)\u003c/p\u003e\n \u003cp\u003e40 (25.3%)\u003c/p\u003e\n \u003cp\u003e4 (2.5%)\u003c/p\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.2 \u0026plusmn; 1.8\u003c/p\u003e\n \u003cp\u003e3.3 \u0026plusmn; 2.0\u003c/p\u003e\n \u003cp\u003e3.3 \u0026plusmn; 2.5\u003c/p\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.439\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Did not complete HS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;HS diploma or GED\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Technical/Vocational\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Some College\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;BS/BA\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;MS/MA/MPH\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;MD/PHD/JD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12 (7.6%)\u003c/p\u003e\n \u003cp\u003e31 (19.6%)\u003c/p\u003e\n \u003cp\u003e10 (6.3%)\u003c/p\u003e\n \u003cp\u003e42 (26.6%)\u003c/p\u003e\n \u003cp\u003e41 (25.9%)\u003c/p\u003e\n \u003cp\u003e8 (5.1%)\u003c/p\u003e\n \u003cp\u003e13 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.1 \u0026plusmn; 1.5\u003c/p\u003e\n \u003cp\u003e3.2 \u0026plusmn; 1.9\u003c/p\u003e\n \u003cp\u003e3.7 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e3.2 \u0026plusmn; 2.0\u003c/p\u003e\n \u003cp\u003e3.1 \u0026plusmn; 1.8\u003c/p\u003e\n \u003cp\u003e3.6 \u0026plusmn; 2.5\u003c/p\u003e\n \u003cp\u003e2.9 \u0026plusmn; 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eEmployment Status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Full time\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Part time\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Unemployed\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Retired\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Housewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53 (33.5%)\u003c/p\u003e\n \u003cp\u003e10 (6.3%)\u003c/p\u003e\n \u003cp\u003e36 (22.8%)\u003c/p\u003e\n \u003cp\u003e46 (29.1%)\u003c/p\u003e\n \u003cp\u003e10 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.8 \u0026plusmn; 1.8\u003c/p\u003e\n \u003cp\u003e3.3 \u0026plusmn; 2.2\u003c/p\u003e\n \u003cp\u003e3.6 \u0026plusmn; 1.7\u003c/p\u003e\n \u003cp\u003e3.2 \u0026plusmn; 2.0\u003c/p\u003e\n \u003cp\u003e3.5 \u0026plusmn;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eHousehold Annual Income\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;$50,000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;$50,001-100,000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;$100,001-150,000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026gt;$150,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36 (22.8%)\u003c/p\u003e\n \u003cp\u003e51 (32.3%)\u003c/p\u003e\n \u003cp\u003e21 (13.3%)\u003c/p\u003e\n \u003cp\u003e12 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.4 \u0026plusmn; 2.0\u003c/p\u003e\n \u003cp\u003e3.1 \u0026plusmn; 1.6\u003c/p\u003e\n \u003cp\u003e3.3 \u0026plusmn; 2.2\u003c/p\u003e\n \u003cp\u003e3.6 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.491\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eCancer Type\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;GI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lung\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;H\u0026amp;N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e58 (36.7%)\u003c/p\u003e\n \u003cp\u003e60 (38.0%)\u003c/p\u003e\n \u003cp\u003e40 (25.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.1 \u0026plusmn; 1.7\u003c/p\u003e\n \u003cp\u003e3.2 \u0026plusmn; 2.0\u003c/p\u003e\n \u003cp\u003e3.4 \u0026plusmn; 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eCaregiver Lives w/ Patient\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e124 (78.5%)\u003c/p\u003e\n \u003cp\u003e34 (21.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.2 \u0026plusmn; 1.6\u003c/p\u003e\n \u003cp\u003e3.2 \u0026plusmn; 1.9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.0443%;\"\u003e\n \u003cp\u003eHistory of Psych Dx\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8093%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20 (12.7%)\u003c/p\u003e\n \u003cp\u003e130 (82.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5526%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.6 \u0026plusmn; 1.8\u003c/p\u003e\n \u003cp\u003e3.1 \u0026plusmn; 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5591%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-1.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eDistress was measured using the MDASI Symptom Interference Score, which is the mean score of six items asking patients how much their symptoms interfere with daily functions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDistress Levels Associated with Cancer-Related Symptoms\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe MDASI was utilized to assess distress related to cancer symptoms.\u0026nbsp;The three highest scoring symptoms were fatigue (mean score 4.78), pain (mean score 4.13), and disturbed sleep (mean score 3.91) (Table 2). Symptom severity varied by tumor type (Figure 1): patients with H\u0026amp;N cancer reported more dry mouth (p=0.012), while those with lung cancer reported more shortness of breath (p \u0026lt;0.001). The mean MDASI symptom interference score, a composite measure of distress, was 3.20, indicating moderate distress overall. However, no statistically significant differences in distress were observed across gender, race, age, cancer type, caregiver type, marital status, education level, health literacy, employment status, income, or psychiatric diagnosis (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eTop 5 Most Severe MDASI Core Symptoms\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMDASI Core Item\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Score\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eYour fatigue at its worst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eYour pain at its worst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eYour disturbed sleep at its worst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e\u0026nbsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eYour problem with lack of appetite at its worst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eYour feeling of being distressed at its worst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003ePatients reported symptom severity on a scale from 0 (\u0026ldquo;not present\u0026rdquo;) to 10 (\u0026ldquo;as bad as you can imagine\u0026rdquo;).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSupportive Care Needs and Their Variation Among Patients\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline SCNS-34 was performed at time of study enrollment to evaluate unmet supportive care needs. The psychological domain had the highest reported needs (mean score 38.20), followed by the health system domain (mean score 35.30) (Table 3). No significant variations in SCNS domain scores were found based on gender, age, race, cancer type, marital status, education level, health literacy, employment status, income, and psychiatric diagnosis history. However, patients who lived with their caregiver reported significantly lower needs in the psychological (p=0.039), patient care and support (p=0.005), physical and daily living (p \u0026lt;0.001), and sexuality domains (p=0.018) compared to those without a live-in caregiver. There was a significant difference in the physical and daily living domain based on caregiver type, with the highest mean score in a patient with an adult son caregiver (n=1); however, conclusions are limited by the small sample size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eSupportive Care Domains Ranked by Highest Need\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCNS-34 Domains\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Score\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e38.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eHealth System\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003ePhysical and Daily Living\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003ePatient Care and Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eSexuality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eResponses are rated on a 5-point Likert scale ranging from 1 (\u0026ldquo;No need\u0026rdquo;) to 5 (\u0026ldquo;High need\u0026rdquo;). Scores were summed for each domain and then standardized to a range from 0 to 100 [17].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAssociations Between Supportive Care Needs and Distress Levels\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the associations between supportive care needs and distress levels, Pearson correlation coefficients were calculated for each SNCS domain using the mean MDASI Symptom Interference. Significant correlations were observed between distress and several domains: psychological (r=0 .342, p \u0026lt;0.001), health system (r=0.253, p=0.001), patient care and support (r=0.237, p=0.003), and physical living and daily living (r=0.378, p \u0026lt;0.001). A trend toward significance was noted for the sexuality domain (r=0.142, p=0.075). Multiple regression analysis was conducted to further assess the relationship between supportive care needs domains and distress, considering all five SCNS domains together. The analysis showed that the combined domains significantly explained variance in distress levels (R2=0.169, p \u0026lt;0.001) (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u003c/strong\u003e Multiple Regression Analysis of Supportive Care Domains as a Predictor of Distress\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCNS Domain\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eHealth System\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003ePatient Care and Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003ePhysical and Daily Living\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e2.705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eSexuality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e-0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-1.192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eR2 = 0.169\u003c/p\u003e\n\u003cp\u003eB: regression coefficient\u003c/p\u003e\n\u003cp\u003eSE: standard error of the regression coefficient\u003c/p\u003e\n\u003cp\u003e\u0026beta;: standardized regression coefficient\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study analyzed the relationship between cancer-related symptoms, supportive care needs, and distress levels among patients with advanced lung, H\u0026amp;N, or GI cancers at the time of treatment initiation. Additionally, it investigated how specific supportive care needs correlate with distress levels and whether demographic or clinical characteristics influence these associations. Our findings contribute to the growing body of literature on the psychosocial needs of patients with advanced cancer and highlight important areas for targeted interventions.\u003c/p\u003e \u003cp\u003eThe results indicate that distress levels, as measured by the MDASI Core Severity Index, were moderate across the sample, with fatigue, pain, and disturbed sleep being the most prevalent patient-reported symptoms. These findings are consistent with prior research indicating that physical symptoms significantly contribute to distress in cancer patients, particularly those with advanced disease stages [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Interestingly, while symptom distress varied by cancer type\u0026mdash;with head and neck cancer patients reporting more dry mouth and lung cancer patients more shortness of breath\u0026mdash;there were no statistically significant differences in overall distress levels based on demographic or clinical characteristics. These findings suggest that the emotional burden of advanced cancer is a pervasive experience, transcending factors such as age, gender, race, and cancer type. This universality may reflect the profound impact of an advanced cancer diagnosis on patients\u0026rsquo; psychological well-being, regardless of individual characteristics. It underscores the need for universal screening and interventions for distress in this population.\u003c/p\u003e \u003cp\u003eWhen considering which patients may need the greatest intervention, our analysis suggests that those with higher psychological and health system needs\u0026mdash;the domains with the highest reported scores\u0026mdash;might benefit most from targeted supportive care interventions. Patients living without a caregiver reported higher needs in these domains, possibly attributed to the lack of immediate emotional and practical support. Caregivers often assist with symptom management, provide psychological comfort, and help navigate the healthcare system. Without this support, patients may feel overwhelmed, leading to increased distress and unmet needs. These findings highlight the critical role caregivers play in the well-being of patients with advanced cancer. Thus, interventions should prioritize psychological support and healthcare system navigation assistance for these patients who might lack the emotional and practical support provided by a caregiver.\u003c/p\u003e \u003cp\u003eThese findings are particularly relevant in light of the recent enactment of the CARE (Caregiver Advise, Record, and Enable) Act in many states across the U.S., which mandates that hospitals identify a designated caregiver upon a patient's discharge and provide the necessary training and information to support at-home care [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Lee et al. found that patients hospitalized in states that had adopted the CARE act reported improved communication with nurses/physicians and more consistent receipt of discharge information when compared to patients in non-CARE states [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Our results suggest that complying with this legislation could have additional benefits beyond legal adherence, especially for chronically ill patients with high symptom burden. By involving caregivers in discharge planning and ensuring they are equipped to support patients, hospitals may effectively reduce patient distress and unmet supportive care needs post-discharge. These results highlight a significant opportunity for healthcare providers to enhance patient outcomes through structured engagement with and education of caregivers.\u003c/p\u003e \u003cp\u003eThe associations between supportive care needs and distress levels were further elucidated through Pearson correlation and regression analyses. Significant correlations were found between distress and several supportive care needs domains, including psychological, health system, patient care and support, and physical and daily living. These findings underscore the interconnectedness of psychological distress and supportive care needs, suggesting that unmet needs in these areas likely contribute to higher distress levels among patients. Thus, patients reporting high needs in these domains\u0026mdash;particularly psychological and health system needs\u0026mdash;are those who may require the greatest intervention to manage distress effectively.\u003c/p\u003e \u003cp\u003eThe strengths of this study include its use of validated instruments to assess both symptom burden and supportive care needs and its inclusion of a diverse population of patients across multiple cancer types, thus enhancing the generalizability of its findings. However, there are limitations to consider. The cross-sectional design limits our ability to establish causality or directionality in the relationships between distress and supportive care needs. Furthermore, the reliance on self-reported data may introduce response bias, particularly concerning sensitive topics such as psychological distress and sexual health. Additionally, the exclusion of non-English-speaking patients may limit generalizability to more diverse populations.\u003c/p\u003e \u003cp\u003eClinically, these findings highlight the importance of integrated care approaches that prioritize both symptom management and supportive care tailored to individual patient needs. Given the benefits of caregiver involvement, healthcare systems should prioritize strategies to engage and educate caregivers effectively, particularly at discharge, to reduce patient distress and unmet needs. Future research should consider longitudinal designs to explore causal pathways between distress and supportive care needs over time, as well as the impact of specific interventions on both symptom burden and perceived supportive care needs. Additionally, exploring the impact of policies like the CARE Act on patient outcomes could provide valuable insights into optimizing care for patients with advanced cancer.\u003c/p\u003e \u003cp\u003eIn conclusion, this study underscores the significant psychosocial and supportive care needs of patients with advanced cancer. Patients with higher psychological and health system needs, especially those lacking caregiver support, may require the greatest intervention to manage their distress effectively. Addressing these needs through comprehensive, patient-centered care may help mitigate distress and improve quality of life, ultimately enhancing outcomes for both patients and their caregivers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eEthics approval and consent to participate:\u003c/u\u003e This study was approved by the Institutional Review Board at Baylor College of Medicine (H-39002) and conducted in accordance with the 1964 Declaration of Helsinki and its later amendments. Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsent for publication\u003c/u\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAvailability of data and materials\u003c/u\u003e: Contact the corresponding author for data requests.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting interests:\u003c/u\u003e Kayla Miranda, Benjamin Musher, and Hoda Badr declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFunding:\u003c/u\u003e This study was funded by the American Cancer Society (RSG 15-058-01 PCSM; PI: Badr). The funders had no role in study design, data collection, analysis, and interpretation, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthors\u0026rsquo; contributions:\u003c/u\u003e All authors contributed to the study conception and design. Material preparation and data collection were performed by Hoda Badr. Data analysis was performed by Kayla Miranda. All authors contributed to drafting the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAcknowledgements\u003c/u\u003e: Not applicable\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRodriguez-Gonzalez A, Velasco-Durantez V, Martin-Abreu C, Cruz-Castellanos P, Hernandez R, Gil-Raga M, Garcia-Torralba E, Garcia-Garcia T, Jimenez-Fonseca P, Calderon C. Fatigue, Emotional Distress, and Illness Uncertainty in Patients with Metastatic Cancer: Results from the Prospective NEOETIC_SEOM Study. Curr Oncol. 2022;29(12):9722\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZabora J, BrintzenhofeSzoc K, Curbow B, Hooker C, Piantadosi S. (2001) The prevalence of psychological distress by cancer site. Psychooncology10(1):19\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarber JM, Weinerman BH, Kuypers JA. Psychosocial Distress in Oncology Outpatients. J Psychosoc Oncol. 1984;2(3\u0026ndash;4):109\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1300/J077v02n03_09\u003c/span\u003e\u003cspan address=\"10.1300/J077v02n03_09\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZabora J, Brintzenhofeszoc K, Curbow B, Hooker C, Piantadosi S. The prevalence of psychological distress by cancer site. Psycho-oncology. 2001;10(1):19\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamer M, Chida Y, Molloy GJ. Psychological distress and cancer mortality. J Psychosom Res. 2009;66(3):255\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Comprehensive Cancer Network. (2024) Distress Management (version 2.2024). Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nccn.org/professionals/physician_gls/pdf/distress.pdf\u003c/span\u003e\u003cspan address=\"https://www.nccn.org/professionals/physician_gls/pdf/distress.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraves KD, Arnold SM, Love CL, Kirsh KL, Moore PG, Passik SD. Distress screening in a multidisciplinary lung cancer clinic: prevalence and predictors of clinically significant distress. Lung Cancer. 2007;55(2):215\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTemel, et al. Early Palliative Care for Patients with Metastatic Non-Small-Cell Lung Cancer. N Engl J Med. 2010;363(8):733\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMirosevic S, Prins JB, Selic P, Zaletel Kragelj L, Klemenc Ketis Z. Prevalence and factors associated with unmet needs in post-treatment cancer survivors: A systematic review. Eur J Cancer Care. 2019;28(3):e13060.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaruso R, Nanni MG, Riba MB, Sabato S, Grassi L. The burden of psychosocial morbidity related to cancer: patient and family issues. Int Rev Psychiatry. 2017;29(5):389\u0026ndash;402. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/09540261.2017.1288090\u003c/span\u003e\u003cspan address=\"10.1080/09540261.2017.1288090\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalker J, et al. Prevalence associations, and adequacy of treatment of major depression in patients with cancer: a cross-sectional analysis of routinely collected clinical data. Lancet Psychiatry. 2014;1(5):343\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZibelli A, Holland K, Wei E. Causes of Cancer Re-Admissions: A Patient-Centered Approach. JCO Oncol Pract. 2020;16(8):e734\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBradley, et al. Working, Low Income, and Cancer Caregiving: Financial and Mental Health Impacts. J Clin Oncol. 2023;41(16):2939\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorris NS, MacLean CD, Chew LD, Littenberg B. The Single Item Literacy Screener: evaluation of a brief instrument to identify limited reading ability. BMC Fam Pract. 2006;7:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCleeland CS, Mendoza TR, Wang XS, et al. Assessing symptom distress in cancer patients: the M.D. Anderson Symptom Inventory. Cancer. 2000;89:1634\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoyes A, Girgis A, Lecathelinais C. Brief assessment of adult cancer patients' perceived needs: Development and validation of the 34-item Supportive Care Needs Survey (SCNS-SF34). J Eval Clin Pract. 2009;15(4):602\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcElduff P, Boyes A, Zucca A, Girgis A. Supportive Care Needs Survey: A guide to administration, scoring and analysis. Newcastle: Centre for Health Research \u0026amp; Psycho-Oncology; 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePodbury B, Gurgenci T, Huggett G, Greer R, Hardy J, Good P. Psychological distress and physical symptoms in advanced cancer: cross-sectional study. BMJ Support Palliat Care. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/spcare-2024-004940\u003c/span\u003e\u003cspan address=\"10.1136/spcare-2024-004940\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee CR, Taggert E, Coe NB, Chatterjee P. Patient Experience at US Hospitals Following the Caregiver Advise, Record, Enable (CARE) Act. JAMA Netw Open. 2023;6(5):e2311253.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-palliative-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pcar","sideBox":"Learn more about [BMC Palliative Care](http://bmcpalliatcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pcar/default.aspx","title":"BMC Palliative Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"advanced cancer, caregiver, distress, supportive care","lastPublishedDoi":"10.21203/rs.3.rs-5875245/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5875245/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e \u003cp\u003ePatients with advanced cancer endure considerable physical and emotional distress without sufficient supportive care. In order to identify areas for intervention, this cross-sectional study examined the relationship between cancer-related symptoms, supportive care needs, and distress levels in patients with advanced lung, head and neck, or gastrointestinal cancers.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBaseline data from 158 patients enrolled in a multisite dyadic interventional study were analyzed using the M.D. Anderson Symptom Inventory (MDASI) and Supportive Care Needs Survey (SCNS-34). Pearson correlations and multiple regression analyses were used to explore associations between supportive care needs and distress.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDistress levels were moderate across the study population, with fatigue, pain, and disturbed sleep being the most reported symptoms. Patients who lived with their caregivers reported significantly lower needs in four out of five domains. Positive correlations were found between distress levels and supportive care needs in the psychological (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), health system (p\u0026thinsp;=\u0026thinsp;0.001), patient care and support (p\u0026thinsp;=\u0026thinsp;0.003), and physical and daily living domains (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multiple regression analysis showed that these domains collectively explained a significant portion of the variance in distress levels (R2\u0026thinsp;=\u0026thinsp;0.169, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIndependent of demographic or clinic characteristics, patients with advanced cancer experience significant distress and unmet supportive care needs, particularly in psychological and health system domains. The association between living with caregivers and lower reported needs suggests that caregiver support may play a crucial role in meeting these needs. Therefore, integrating strategies that involve and support caregivers could potentially reduce distress and improve the quality of life for patients with advanced cancer.\u003c/p\u003e","manuscriptTitle":"Unmet supportive care needs in patients with advanced cancer and its impact on distress","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-03 09:15:52","doi":"10.21203/rs.3.rs-5875245/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-06T03:45:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-19T12:28:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-13T19:27:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-13T11:39:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203378079342110223385818817585964196885","date":"2025-02-13T09:23:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-12T07:55:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"158392367164950828484904452937041986036","date":"2025-02-07T19:02:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92215821981522548921069144827299542287","date":"2025-02-07T16:01:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-07T13:59:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"123085792082260147345397618422547011146","date":"2025-02-07T12:49:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271164233578275444677048437489597863258","date":"2025-02-07T12:33:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-07T08:11:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-01-29T06:05:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-27T13:04:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-27T13:03:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Palliative Care","date":"2025-01-21T17:50:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-palliative-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pcar","sideBox":"Learn more about [BMC Palliative Care](http://bmcpalliatcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pcar/default.aspx","title":"BMC Palliative Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c5daafa0-03fa-4df5-91b6-443a5ca6410a","owner":[],"postedDate":"February 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T16:03:32+00:00","versionOfRecord":{"articleIdentity":"rs-5875245","link":"https://doi.org/10.1186/s12904-025-01746-x","journal":{"identity":"bmc-palliative-care","isVorOnly":false,"title":"BMC Palliative Care"},"publishedOn":"2025-04-21 15:57:12","publishedOnDateReadable":"April 21st, 2025"},"versionCreatedAt":"2025-02-03 09:15:52","video":"","vorDoi":"10.1186/s12904-025-01746-x","vorDoiUrl":"https://doi.org/10.1186/s12904-025-01746-x","workflowStages":[]},"version":"v1","identity":"rs-5875245","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5875245","identity":"rs-5875245","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}