Unmet Needs and Receipt of Supportive Care Services in Head and Neck Cancer Patients Prior to Oncologic Treatment: A Prospective,Cross-Sectional Pilot Study

Abstract

Objective:

To characterize the supportive care (SC) needs and receipt of SC services among head and neck cancer (HNC) patients prior to oncologic treatment and to explore the influence of social determinants of health on these outcomes.

Materials and Methods:

Newly diagnosed HNC patients were surveyed via telephone prior to oncologic treatment between 10/2019 and 1/2021 using a prospective, cross-sectional, bi-institutional, pilot study design. The primary study outcome was unmet SC needs (Supportive Care Needs Survey-Short Form34 [SCNS-SF34]). Hospital type (university- vs county safety-net) was explored as an exposure. Descriptive statistics were performed using STATA16 (College Station, TX).

Results:

Among 158 potentially eligible patients, 129 were successfully contacted, 78 met the study criteria, and 50 completed the survey. The mean age was 61, 58% exhibited clinical stage III-IV disease, and 68% and 32% were treated at the university and county safety-net hospital, respectively. Patients were surveyed a median of 20 days after their first oncology visit and 17 days prior to initiation of oncology treatment. They had a median of 24 total needs (11 were met and 13 were unmet) and preferred to see a median of 4 SC services but received care from none. County safety-net patients had comparatively more unmet needs than university patients (14.5 vs 11.5, P = .04).

Conclusion:

Pretreatment HNC patients at a bi-institutional academic medical center report a high number of unmet SC needs with corollary poor receipt of available SC services. Novel interventions to address this significant gap in care are needed.

Keywords

head and neck cancer pretreatment survivorship care supportive care unmet needs

Introduction

Supportive care (SC) needs in head and neck cancer (HNC) patients are common and poorly managed, resulting in poor patient health outcomes. In the United States, over 65,000 patients are diagnosed with HNC annually.¹ Among these patients, tobacco use, problem-drinking, depression and distress are prevalent, inadequately managed, and often persist after treatment.^2-15 Failure to address these issues in cancer patients has been associated with compromised health outcomes including increased rates of cancer recurrence and decreased survival.^16-23

There are 2 key barriers to improved management of SC needs in newly-diagnosed HNC patients. First, self-reported, unmet needs of HNC patients prior to starting oncologic treatment have not been well-characterized. A few studies of posttreatment survivors reported that approximately 50% to 75% of patients report at least one unmet need,^8-10 and the average patient reports 6 unmet needs.^8-10 Second, although essential for the delivery of patient-centered care, HNC patient preference for, referral to, and receipt of supportive services prior to oncologic treatment has received little examination.

In this study, we aimed to: (1) describe the unmet needs of newly-diagnosed HNC patients prior to treatment; (2) explore patient- and tumor-level influences of unmet needs prior to treatment; and (3) evaluate pretreatment use of available SC services. Additionally, the high burden of social determinants of health (SDOH) in HNC survivors are linked to numerous adverse oncologic outcomes,^24-33 yet associations between SDOH and SC needs and use of SC services have not been described. We sought to investigate this gap in knowledge by evaluating hospital type (university vs county safety-net) as an exploratory exposure of interest. An improved understanding of unmet pretreatment needs, their influences, and use of available SC services can inform interventions to improve SC delivery and outcomes.

Methods

Population and Study Setting

An Institutional Review Board-approved prospective cohort study (STU2019-0613) was conducted at UT Southwestern Medical Center (UTSW; university hospital) and Parkland Hospital (PH; county safety-net hospital) in Dallas, Texas from October 2019 to January 2021. Approximately 350 newly diagnosed mucosal HNC patients are treated at these institutions annually. Eligible patients were identified from: a weekly new patient referral report at UTSW; Parkland HNC clinic providers alerting study staff in a manual, opportunistic fashion; and weekly bi-institutional tumor board reports (Figure 2). Screening criteria included an invasive cancer diagnosis, patient awareness of their diagnosis, and presentation to the UTSW or Parkland head and neck surgical oncology clinic. Eligible cancer diagnoses included mucosal carcinomas of the head and neck, head and neck sarcoma, and malignant salivary neoplasms. The study was placed on hold during the early phase of the COVID-19 pandemic (April 2020 to May 2020).

Enrollment Methodology

A block enrollment strategy according to anatomic subsite (oropharynx vs oral cavity vs other) and hospital location (university vs county safety-net) was employed to ensure enrollment of a representative sample of patients (Figure 1). Thresholds for each group were determined according to historical bi-institutional data. Once the cap for a specific institution and subsite was reached, recruitment of HNC patients with these characteristics was discontinued. Potentially eligible patients were given a study information sheet in-person by clinical staff, via MyChart, or by mail. The recruitment team then called eligible patients to obtain verbal informed consent and to complete the survey over the phone. Patients not reached after 6 call attempts or before treatment initiation, who did not consent, or were deemed ineligible due to physical or mental impairment were excluded. Several patients with advanced or laryngeal cancer presented with a communication impairment and were either unintelligible by phone or could not carry-on prolonged conversations due to pain or fatigue from speaking (Figure 1). To accommodate these types of patients, we modified the protocol and allowed patients to designate a partner to communicate their responses. Participants successfully completing the telephone survey were mailed a $25 gift card.

Survey

The survey included sociodemographics and 8 different validated measurement tools (total: 71 questions). These included the National Comprehensive Cancer Network (NCCN) Distress Thermometer (1 question), SC Needs Survey-Short Form (SCNS SF-34; 33 questions); General Self Efficacy Scale (10 questions), Cancer Tobacco Use Questionnaire-Core (CTUQ-Core; 4 questions), Alcohol Use Disorders Identification Test-C (AUDIT-C; 3 questions), Patient Health Questionnaire-8 (PHQ-8; 8 questions), EuroQol Health Questionnaire (EQ5D-5L; 5 questions). In the SCNS SF-34, the question about fear of recurrence was eliminated since it was not relevant for a pretreatment population (i.e., only 33 items were asked).

To orient the reader to the SCNS SF-34 (ie, the primary outcome measure), Question #1 of the measure asked, “In the last month, what was your level of need for help with [pain]?” Participants were given 5 response options: (1) “not applicable” (not a problem for the “patient”); (2) “satisfied” (they needed help but the need was met); (3) “low need” (the item caused concern or discomfort; the patient had “little” need for additional help); (4) “moderate need” (the patient had “some” need for additional help); (5) “high need” (the patient had “strong” need for additional help). In this scenario, participants either did not have a need for help with pain (ie, response #1 above), had a need for help with pain and that need was met (ie, response #2 above), or had a need for help with pain and that need was not met (ie, responses #3-5, which distinguished the severity of the need for help with pain). Survey responses were recorded using REDCap^34,35 electronic data capture tool.

Primary Outcome and Other Exploratory Variables

The primary study outcome was the number of unmet SC needs (SCNS-SF). The exploratory exposure was university- versus county safety-net hospital location. The exploratory outcome was receipt of available supportive care services.

Statistical Analyses

STATA16 (College Station, TX) was used for descriptive statistical analyses. Pearson’s chi-squared, Fisher’s exact, Wilcoxon-Mann-Whitney, and student t-tests were used to compare sociodemographic variables according to hospital system. Statistical significance was defined as P < .05 and all P-values were reported as 2-sided.

Data Availability

Data were generated by the authors and are available upon request.

Results

Study Recruitment

Among 173 potentially eligible patients, 161 were called and 129 patients were successfully reached between October 2019 to January 2020 (Figures 1 and 2). Among these 129 patients, several were found to be ineligible due to: study-related criteria (n = 5), language-related criteria (n = 2), health-related criteria (n = 23 [unable to effectively communicate via phone prior to the IRB modification]), and treatment-related criteria (n = 21). An additional 28 patients declined to participate and 50 patients ultimately completed the survey (Figure 2). There was no difference in sociodemographic, select behavioral or oncologic characteristics between the included (n = 50) and excluded (n = 108) groups (Supplemental Table 1). Of note, however, a higher proportion of excluded patients (56%) underwent primary surgery compared to patients who were included in the study (36%).

Patient, Tumor, and Treatment Characteristics

The mean age of our patient sample was 61, 72% were male, 71% were non-Hispanic white, 58% presented with AJCC eighth edition overall clinical stage III-IV disease, 68% were treated at a university hospital system, and 32% were treated at a county safety-net hospital system (Table 1). The distribution of patients according to anatomic tumor subsite was: oral cavity (26%); oropharynx (30%); larynx (30%); and other (14%). The vast majority of patients presented with a new HNC diagnosis (86%) and the remainder presented with recurrent disease.

Table 1.

Demographic and Tumor Characteristics of Head and Neck Cancer Patients.

Variable	Total # (%) N = 50	University # (%) N = 34	County # (%) N = 16	P-value
Sex				.726
Female	14 (28)	9 (26)	5 (31)
Male	36 (72)	25 (74)	11 (69)
Age, mean (SD)	61 (13)	62 (15)	58 (9.5)	.281
Race and Ethnicity (n = 42)				<.001
Non-Hispanic White	30 (71)	24 (89)	6 (40)
Hispanic, any race	7 (17)	1 (4)	6 (40)
Non-Hispanic Black	3 (7)	0 (0)	3 (20)
Non-Hispanic Asian	2 (5)	2 (7)	0 (0)
Education				.159
High school or less	24 (48)	14 (41)	10 (63)
More than high school	26 (52)	20 (59)	6 (38)
Insurance				<.001
Not insured	10 (20)	0 (0)	10 (63)
Private insurance	21 (42)	20 (59)	1 (6)
Medicaid	3 (6)	0 (0)	3 (19)
Medicare	16 (32)	14 (41)	2 (13)
Annual household income (n = 46)				<.001
Less than $25 000	15 (33)	5 (15)	10 (77)
Greater than $25 000	31 (67)	28 (85)	3 (23)
Has primary medical doctor (n = 31)				.097
Yes	23 (74)	15 (88)	8 (57)
No	8 (26)	2 (12)	6 (43)
Satisfied with care (n = 23)	22 (96)	14 (93)	8 (100)	1.000
ACE27 comorbidity score				.061
0-1	34 (68)	26 (76)	8 (50)
2-3	16 (32)	8 (24)	8 (50)
Subsite				.714
Oral cavity	13 (26)	9 (26)	4 (25)
P16+ oropharynx	12 (24)	8 (24)	4 (25)
P16− oropharynx	3 (6)	2 (6)	1 (6)
Larynx	15 (30)	11 (32)	4 (25)
Hypopharynx	3 (6)	2 (6)	1 (6)
Nasopharynx	0 (0)	0 (0)	0 (0)
Sinonasal	1 (2)	0 (0)	1 (6)
Salivary gland	2 (4)	2 (6)	0 (0)
Unknown primary	1 (2)	0 (0)	1 (6)
Histology				1.000
Mucosal squamous cell carcinoma	46 (92)	31 (91)	15 (94)
Salivary gland carcinoma	2 (4)	2 (6)	0 (0)
Sarcoma	2 (4)	1 (3)	1 (6)
Treatment Paradigm				.512
Surgery alone	12 (24)	9 (26)	3 (19)
Surgery + RT	5 (10)	4 (12)	1 (6)
Surgery + CRT	1 (2)	0 (0)	1 (6)
Neoadjuvant chemo + surgery	2 (4)	2 (6)	0 (0)
Definitive radiation	3 (6)	3 (9)	0 (0)
Definitive chemoradiation	24 (50)	15 (44)	10 (63)
Neoadjuvant chemo + CRT	2 (4)	1 (3)	1 (6)
Clinical TNM Staging, eighth Ed
Clinical eighth ed stage				.143
I	10 (20)	9 (26)	1 (6)
II	11 (22)	8 (24)	3 (19)
III	9 (18)	7 (21)	2 (13)
IV	20 (40)	10 (29)	10 (63)
M1	3 (6)	3 (9)	0 (0)	.542
Recurrence				.666
Primary tumor	43 (86)	30 (88)	13 (81)
Recurrence	7 (14)	4 (11)	3 (19)

Note. Race/ethnicity, education, income, primary care attachment, and satisfaction were collected via survey. Sex, age, ACE27 score, subsite, histology, treatment paradigm, and clinical stage were collected via medical record abstraction. All variables with n < 50 are due to respondents not knowing or choosing not to answer. Income threshold is set at $25 000 to be close to the 2021 federal poverty level for a household of four.³⁶

Collectively, the cohort (n = 50) exhibited several SDOH and risky health behaviors associated with poor health outcomes. One-third met criteria for poverty (gross annual household income less than $25 000, assuming a 4-person household); 18% currently smoked cigarettes; 26% were hazardous drinkers; 56% exhibited clinically significant distress; 30% had major depression (Tables 1 and 2). There were significant differences in SDOH across hospital systems. Compared to university patients, county patients were more likely to report being uninsured, an annual gross income less than $25 000 (77% vs 15%, P < .001), and hazardous drinking habits (50% vs 15%, P < .01).

Table 2.

Behavioral, Psychologic, and Health-Related Quality of Life Survey Results.

Cancer Patient Tobacco Use Questionnaire (C-TUQ)—Core
Variable	Total N = 50	University N = 34	County N = 16	P-value
Pack-years median (IQR) (n = 33)	20 (10-33)	19.4 (3.8-30)	30 (10-40)	.120
Tobacco usage, # (%)				.788
Never	16 (32)	12 (35)	4 (25)
Former	25 (50)	16 (47)	9 (56)
Current	9 (18)	6 (18)	3 (19)
Alcohol Use Disorders Identification Test (AUDIT-C)
Variable	Total N = 48	University N = 32	County N = 16	P-value
AUDIT-C score (0-12), median (IQR)	1 (0-3)	1 (0-2)	3 (0-5)	.040
Hazardous drinking (men $\geq 4$ or women $\geq 3$ ), # (%)	13 (26)	5 (15)	8 (50)	.008
General Self-Efficacy Scale (GSE)
Variable	Total N = 45	University N = 31	County N = 14	P-value
Self-efficacy score (10-40), median (IQR)	34 (31-37)	33 (31-38)	34.5 (29-37)	.554
Self-efficacy				.180
At or above international average	38 (84)	28 (90)	10 (71)
Below international average	7 (16)	3 (10)	4 (29)
Personal Health Questionnaire Depression Scale (PHQ-8)
Variable	Total N = 44	University N = 32	County N = 12	P-value
PHQ-8 score (0-24), median (IQR)	6 (3.5-10.5)	5 (2-9.5)	8.5 (5-12)	.086
Major depression (score $\geq 10$ ), # (%)	13 (30)	8 (25)	7 (58)	.281
Health-Related Quality of Life—EQ5D (1-5)
Variable	Total N = 50	University N = 34	County N = 16	P-value
Mobility
Score, median (IQR)	1 (1-2)	1 (1-1)	1 (1-2)	.269
Any problems, # (%)	15 (30)	8 (24)	7 (44)	.146
Self-care
Score, median (IQR)	1 (1-1)	1 (1-1)	1 (1-1)	.916
Any problems, # (%)	3 (6)	2 (6)	1 (6)	1.000
Usual activities (n = 49)
Score, median (IQR)	1 (1-2)	1 (1-2)	2 (2-3)	.009
Any problems, # (%)	24 (49)	12 (35)	12 (80)	.005
Pain or discomfort
Score, mean (SD)	2.6 (1.5)	2.7 (1.7)	2.4 (1.1)	.563
Any problems, # (%)	35 (70)	22 (65)	13 (81)	.328
Anxiety or depression
Score, mean (SD)	3.1 (1.7)	3.1 (1.8)	3.1 (1.7)	.995
Any problems, # (%)	36 (72)	24 (71)	12 (75)	1.000
NCCN Distress Thermometer
Variable	Total N = 50	University N = 34	County N = 16	P-value
Distress score (0-10), mean (SD)	4.2 (3.1)	3.9 (2.7)	4.9 (3.9)	.332
Clinically significant distress (score $\geq 4$ ), # (%)	28 (56)	19 (56)	9 (56)	.981

Note. All variables were collected via survey. Variables with n < 50 are due to respondents not knowing, choosing not to answer, or question not applicable (pack years). AUDIT-C was scored on a scale from 0 to 12 with 0 being no alcohol use and 12 being the most alcohol use. Hazardous drinking was defined as a score of 4 or more in men and 3 or more in women. General self-efficacy was scored on a scale from 10 to 40 with a higher score indicating more self-efficacy. International average self-efficacy score of 29.55 is used as a cutoff.³⁷ PHQ-8 asks about depressive symptoms experienced over the last 2 weeks with the threshold of major depression being a score of 10 or more. EQ5D-5L health related quality of life was scored on a scale from 1 to 5 with 1 = no problems, 2 = slight problems, 3 = moderate problems, 4 = severe problems, 5 = unable. Distress was measured on the National Comprehensive Cancer Center Distress Thermometer scale with 0 being no distress and 10 being severe distress.

Treatment and Study Timing Characteristics

The median number of days from referral to first oncology visit was 9 (interquartile range [IQR]: 5-14 days; Supplemental Table 2). The median number of days from first oncology clinic visit to (1) survey was 20 (IQR: 11-25 days) and (2) treatment initiation was 37 (IQR: 23.5-60 days).

Unmet Supportive Care Needs

Out of 33 possible needs, patients had a median of 13 unmet needs (Table 3) and 24 total needs (11 of which were met). Nearly all patients (98%) had at least one unmet need, and 72% of patients had at least one high unmet need. Needs tended to be most prevalent in the (1) psychological, (2) physical and daily living, and (3) health system and information needs domains, though median scores suggest that these unmet needs are mild overall. Over half of patients reported “uncertainty about the future” and “fear of cancer spreading” as moderate unmet needs.

Table 3.

Supportive Care Needs.

SCNS-SF34 Scores for Each Supportive Care Need (1-5)
Supportive Care Need	Total, median (IQR) N = 50
Psychological Needs (10-50)	26 (20-34)
Uncertainty about the future	4 (3-5)
Fears about the cancer spreading	4 (2-5)
Concerns about the worries of those close to you	3 (2-4)
Anxiety	3 (1-4)
Feeling down or depressed	3 (1-4)
Worry that the results of treatment are beyond your control	3 (1-4)
Learning to feel in control of your situation	3 (1-4)
Keeping a positive outlook	2 (1-4)
Feelings about death and dying	2 (1-3)
Feelings of sadness	1.5 (1-3)
Physical and Daily Living Needs (5-25)	14 (7-17)
Pain	3 (1-4)
Tired or lack of energy	3 (1-4)
Not being able to do the things you used to do	3 (1-4)
Feeling unwell	2 (1-4)
Doing work around the home	2 (1-3)
Health System & Information Needs* (10-50)	24 (19-33)
Being informed about things you can do to help yourself get well	3 (2-4)
Being given information (written, diagrams, drawings) about aspects of managing your illness and side-effects at home	2 (2-4)
Being given explanations of those tests for which you would like explanations	2 (2-4)
Being adequately informed about the benefits and side-effects of treatments before you choose to have them	2 (2-4)
Being informed about your test results as soon as feasible	2 (2-4)
Having one member of the clinic staff with whom you can talk to about all aspects of your condition, treatment and follow-up	2 (2-4)
Being given written information about the important aspects of you care	2 (2-3)
Being treated like a person and not just another case	2 (2-3)
Being treated in a clinic that looks as physically pleasant as possible	2 (2-3)
Having access to professional counseling (eg, psychologist, social worker, counselor, nurse specialist) if you/family/friends need it	2 (1-3)
Patient Care & Support Needs (5-25)	10 (9-14)
Having more choice of clinic	2 (2-3)
Getting reassurance from the medical staff that the way you feel is normal	2 (2-3)
Clinic staff properly attending to your physical needs	2 (2-3)
Clinic staff acknowledging and showing sensitivity to your feelings and emotional needs	2 (2-2)
Having more choice about cancer specialist	2 (2-2)
Sexuality Needs (3-15)	4 (3-6)
Changes in sexual feelings	1 (1-2)
Changes in your sexual relationship	1 (1-2)
Being given information about sexual relationships	1 (1-2)
Prevalence Rates of Met and Unmet Needs	Total,# (%) N = 50
Met needs
Number, median (IQR)	11 (5-14)
Patients with >30	0
Patients with >20	2 (4)
Patients with >10	26 (52)
Patients with >5	37 (74)
Patients with any	48 (96)
Variable	Total,# (%) N = 50
Low, moderate, or high unmet needs
Number, median (IQR)	13 (8-18)
Patients with >30	1 (2)
Patients with >20	10 (20)
Patients with >10	32 (64)
Patients with >5	41 (82)
Patients with any	49 (98)
Moderate or high unmet needs
Number, median (IQR)	8 (5-13)
Patients with >30	1 (6)
Patients with >20	7 (14)
Patients with >10	21 (42)
Patients with >5	31 (62)
Patients with any	46 (92)
High unmet needs
Number, median (IQR)	2 (0-6)
Patients with >30	0
Patients with >20	1 (2)
Patients with >10	5 (10)
Patients with >5	16 (32)
Patients with any	36 (72)

Note. Supportive care needs results are reported from the SCNS-SF34 survey administered to n = 50 patients. For each need, a score of 1 represents no need, 2 represents a need that was met, 3 represents a mild unmet need, 4 represents a moderate unmet need, and 5 represents a high unmet need. Domain scores were calculated as a summated Likert scale for each domain. One information need item, “to be informed about cancer which is under control or diminishing (ie, remission),” was omitted from the survey because it did not pertain to the pretreatment period.

While both university and county safety-net patients reported many unmet needs, the latter group reported more unmet needs of any kind (median: 14.5 vs 11.5, P = .04), more moderate or high unmet needs (median: 13.5 vs 6.5, P < .001) and more high unmet needs (6.5 vs 1.5, P = .02; Supplemental Table 3). Compared to the university patients, county safety-net patients had significantly higher physical and daily living needs (median domain score: 17.5 vs 11.5, P < .01), health system and information needs (median domain score: 29.5 vs 22, P = .01), and patient care and support needs (median domain score: 13 vs 10, P = .049).

Use of Supportive Care Services

Despite the high prevalence of unmet needs, patients infrequently received SC services designed to address these needs prior to oncologic treatment. Among 13 available services, patients reported preferring a median of 4 SC services but received care from none. Among the most common services preferred, receipt of care was still low. Whereas 62% of patients preferred to see cancer rehabilitation, only 2% received the service (Figure 3). In general, despite higher needs and more prevalent socioeconomic risk factors, county safety-net patients were not more likely than university patients to want, hear about, discuss, be referred to, or utilize SC services. For example, safety-net patients were more likely to report problems with usual activities (80% vs 35%, P < .01), but were not significantly more likely to want, hear about, discuss, be referred to, or utilize cancer rehabilitation services.

Multiple factors may have contributed to poor receipt of SC services. For instance, lack of patient awareness of music therapy played a role: 38% of our cohort would have preferred to receive music therapy (after learning about it during the survey) but only 18% had heard of it in the clinical context. Poor awareness or prioritization of SC services by clinicians also likely contributed. While 62% of patients preferred to see cancer rehabilitation, recommendation for (18%) and referral to (14%) this service was low. Finally, some patients exhibited low desire for a service despite high need. Among 13 patients with hazardous drinking, 38% were aware of addiction psychiatry, yet only 23% desired the service (Supplemental Figure 1).

A minority of patients with current smoking, hazardous alcohol use, or depression received indicated SC services. Only 11% of current smokers (n = 9) were seen by the institutional tobacco treatment program, which employs bi-modal pharmacotherapy and behavioral therapy (Supplemental Figure 1). Although 13 patients exhibited hazardous drinking, only one (8%) saw addiction psychiatry. Among 13 patients with depression, none were seen by cancer psychology and only one (8%) saw psychiatry.

Discussion

These data demonstrate that our bi-institutional pretreatment HNC population exhibited a high burden of SDOH and reported a high number of unmet needs. County safety-net hospital type was associated with a greater number of unmet needs. SC services designed to address these unmet needs were underutilized in the pretreatment period, even by the safety-net population. Low patient and clinician awareness of SC services, low referrals, and low patient interest all contributed to low SC service utilization.

Cohort Characteristics and Disparities

The pretreatment prevalence of sociodemographic, risky health behaviors, and mental health characteristics of our HNC patients reflect the national population.^2,4-7,11,12 Low utilization of available SC services suggests these behavioral and psychologic problems were not addressed prior to treatment. Given their impact on perioperative complications, adherence to radiation treatment, radiation toxicity and oncologic outcomes, failure to address these issues during the pretreatment period reflects a missed opportunity to improve care and quality of life.

Unmet Needs

Our cross-sectional pretreatment patient sample exhibited a high burden of unmet needs: 98% of patients had at least one unmet need prior to treatment, and patients reported a median of 13 unmet needs. According to one study of primarily post-treatment HNC survivors, 60% exhibited at least one unmet need and survivors reported a median of 6 unmet needs.⁸ Prior investigators have noted that “earlier phase” in HNC survivorship was associated with more unmet needs.^8-10 Our data strongly corroborates this finding and suggests that the pretreatment survivorship phase constitutes a time of profound need for HNC patients.

Among the 5 domains of need according to the SCNS SF-34, unmet psychologic and physical and daily living needs constituted the highest burden and severity of unmet needs. Discrete services and providers are available to help patients address their anxiety, depression, pain, and fatigue. Oncologists should prioritize screening for these mental and physical health problems and refer to or co-manage them with primary care, behavioral health services, psychiatry, pain management, physical medicine and rehabilitation, or palliative and supportive care. Some psychologic needs, such as “uncertainty about the future” and “fear of cancer spreading” do not have accompanying, definitively effective, interventions. Evidence-based treatment such as promotion of coping strategies, support groups, counseling, and cognitive behavioral therapy may be employed.^38-40 Future research to identify effective interventions for these needs is warranted.

In our exploratory analysis, the number and severity of unmet needs were significantly higher among county safety-net HNC patients relative to university patients. County patients had a significantly higher median number of moderate and high unmet needs, particularly in the psychologic, physical activity and daily living and health system information domains. Standardized, systematic, comprehensive SC screening and management protocols may be even more essential for this population of patients. Our safety-net health system is considering strategies for augmenting wellness education, testing, and explanation of test results to better meet patients’ information needs.

SC Service Awareness and Utilization

Even though patients reported that they wanted SC services, very few established care with these services in the pretreatment period. Lack of knowledge of services, infrequent discussions with care team members, and low numbers of referrals all contributed to low SC service utilization. Since such a low proportion of patients discussed services with their team, were referred, or were seen, it is difficult to draw conclusions about which step of the process most precluded utilization of any given service. Further investigation is needed to better understand why pretreatment patients infrequently use SC services.

We surmise that several practice, provider, and patient-level barriers contribute to the high level of unmet needs and low level of service utilization overall. For one, the window for SC intervention between referral and initiation of oncologic treatment is only several weeks.^41-43 Patients tend to already be overwhelmed by their work-up and oncology treatment planning.⁴⁴ They may perceive they are unable to meaningfully address these ancillary SC needs in such a short time frame. If this is the case, patient education and implementation of processes that accelerate screening and referral may facilitate greater SC service utilization and decreased unmet needs.

It is also likely that providers are unaware of the various existing SC services, so that even if a patient expresses a need, the provider may not appropriately refer the patient.^45-47 For this barrier, increasing provider awareness may be warranted. Finally, patients may not be able to communicate needs to their provider due to the limited time in a visit or difficulty speaking.^14,45,48-50 A separate, comprehensive screening process for SC needs would help the care team to know about and act upon the most important needs for a given patient in a timely manner.

Limitations

This study exhibits several limitations which constrain the generalizability of the findings. Although a prospective observational design was applied, this study recruited only 50 patients from 2 institutions with academic affiliations in Dallas, Texas. A higher-than-usual number of patients treated with curative intent had distant metastases (n = 3). Although HNCs are classically comprised of mucosal squamous cell carcinomas and salivary gland carcinomas, 4% of our cohort had head and neck sarcomas. Since the survey did not include any COVID-19 pandemic-related questions, the influence of the pandemic on study outcomes is not evaluable in this study. Fortunately, qualitative data was also collected, and is reported in an accompanying study. Finally, a portion of patients may have had their needs met or seen indicated SC services after our survey and before treatment.

Conclusion

Pretreatment HNC patients commonly exhibit health disparities and numerous unmet SC needs, yet infrequently use available SC services. Considering the high prevalence of SC needs that adversely influence survival in this population, interventions to address this gap in care are needed.

Supplemental Material

sj-docx-1-aor-10.1177_00034894231154182 – Supplemental material for Unmet Needs and Receipt of Supportive Care Services in Head and Neck Cancer Patients Prior to Oncologic Treatment: A Prospective, Cross-Sectional Pilot Study

Supplemental material, sj-docx-1-aor-10.1177_00034894231154182 for Unmet Needs and Receipt of Supportive Care Services in Head and Neck Cancer Patients Prior to Oncologic Treatment: A Prospective, Cross-Sectional Pilot Study by Andrew T. Day, Courtney A. Prestwood, Thomas R. Emmett, Rebecca L. Eary, Jordan R. Salley, Vanessa Cerda, Elizabeth Mayfield Arnold, Simon Craddock Lee and Jasmin A. Tiro in Annals of Otology, Rhinology & Laryngology

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: American Cancer Society Institutional Research Grant (IRG# 17-143-13).

Eugene P. Frenkel, M.D. Scholar in Clinical Medicine Award

ORCID iDs

Andrew T. Day

Rebecca L. Eary

Simon Craddock Lee

Supplemental Material

Supplemental material for this article is available online.

References

Siegel

Miller

Fuchs

Jemal

Cancer Statistics, 2021. CA Cancer J Clin. 2021;71(1):7-33.

Burris

Studts

DeRosa

Ostroff

JS.

Systematic review of tobacco use after lung or head/neck cancer diagnosis: results and recommendations for future research. Cancer Epidemiol Biomarkers Prev. 2015;24(10):1450-1461.

Ostroff

Jacobsen

Moadel

, et al. Prevalence and predictors of continued tobacco use after treatment of patients with head and neck cancer. Cancer. 1995;75(2):569-576.

Chan

Irish

Wood

, et al. Smoking cessation in patients diagnosed with head and neck cancer. J Otolaryngol. 2004;33(2):75-81.

Lydiatt

Moran

Burke

WJ.

A review of depression in the head and neck cancer patient. Clin Adv Hematol Oncol. 2009;7(6):397-403.

Misono

Weiss

Fann

Redman

Yueh

Incidence of suicide in persons with cancer. J Clin Oncol. 2008;26(29):4731-4738.

Duffy

Ronis

Valenstein

, et al. Depressive symptoms, smoking, drinking, and quality of life among head and neck cancer patients. Psychosomatics. 2007;48(2):142-148.

Giuliani

McQuestion

Jones

, et al. Prevalence and nature of survivorship needs in patients with head and neck cancer. Head Neck. 2016;38(7):1097-1103.

O’Brien

Timmons

Butow

, et al. Associations between neighbourhood support and financial burden with unmet needs of head and neck cancer survivors. Oral Oncol. 2017;65:57-64.

10.

Wells

Cunningham

Lang

, et al. Distress, concerns and unmet needs in survivors of head and neck cancer: a cross-sectional survey. Eur J Cancer Care. 2015;24(5):748-760.

11.

Krebber

Jansen

Cuijpers

Leemans

Verdonck-de Leeuw

IM.

Screening for psychological distress in follow-up care to identify head and neck cancer patients with untreated distress. Supp Care Cancer. 2016;24(6):2541-2548.

12.

Ghazali

Roe

Lowe

, et al. Screening for distress using the distress thermometer and the University of Washington quality of life in post-treatment head and neck cancer survivors. Eur Arch Otorhinolaryngol. 2017;274(5):2253-2260.

13.

Druesne-Pecollo

Keita

Touvier

, et al. Alcohol drinking and second primary cancer risk in patients with upper aerodigestive tract cancers: a systematic review and meta-analysis of observational studies. Cancer Epidemiol Biomarkers Prev. 2014;23(2):324-331.

14.

Chen

Daly

Vazquez

, et al. Depression among long-term survivors of head and neck cancer treated with radiation therapy. JAMA Otolaryngol Head Neck Surg. 2013;139(9):885-889.

15.

Ninu

Miccinesi

Bulli

, et al. Psychological distress and health-related quality of life among head and neck cancer patients during the first year after treatment. Tumori. 2016;102(1):96-102.

16.

Pinquart

Duberstein

PR.

Depression and cancer mortality: a meta-analysis. Psychol Med. 2010;40(11):1797-1810.

17.

Satin

Linden

Phillips

MJ.

Depression as a predictor of disease progression and mortality in cancer patients: a meta-analysis. Cancer. 2009;115(22):5349-5361.

18.

Deleyiannis

Thomas

Vaughan

Davis

Alcoholism: independent predictor of survival in patients with head and neck cancer. J Natl Cancer Inst. 1996;88(8):542-549.

19.

Duffy

Ronis

McLean

, et al. Pretreatment health behaviors predict survival among patients with head and neck squamous cell carcinoma. J Clin Oncol. 2009;27(12):1969-1975.

20.

Lahart

Metsios

Nevill

Carmichael

AR.

Physical activity, risk of death and recurrence in breast cancer survivors: a systematic review and meta-analysis of epidemiological studies. Acta Oncol. 2015;54(5):635-654.

21.

Mishra

Scherer

Snyder

Geigle

Berlanstein

Topaloglu

Exercise interventions on health-related quality of life for people with cancer during active treatment. Cochrane Database Syst Rev. 2012;2012(8):Cd008465.

22.

Collins

Geller

Antoni

, et al. Sleep duration is associated with survival in advanced cancer patients. Sleep Med. 2017;32:208-212.

23.

Palesh

Aldridge-Gerry

Zeitzer

, et al. Actigraphy-measured sleep disruption as a predictor of survival among women with advanced breast cancer. Sleep. 2014;37(5):837-842.

24.

Naghavi

Echevarria

Strom

, et al. Treatment delays, race, and outcomes in head and neck cancer. Cancer Epidemiol. 2016;45:18-25.

25.

Nichols

Bhattacharyya

Racial differences in stage and survival in head and neck squamous cell carcinoma. Laryngoscope. 2007;117(5):770-775.

26.

Choi

Terrell

Fowler

, et al. Socioeconomic and other demographic disparities predicting survival among head and neck cancer patients. PLoS One. 2016;11(3):e0149886.

27.

Carey

Parasher

Workman

, et al. Disparities in sinonasal squamous cell carcinoma short- and long-term outcomes: analysis from the national cancer database. Laryngoscope. 2018;128(3):560-567.

28.

Molina

Cheung

Perez

, et al. African American and poor patients have a dramatically worse prognosis for head and neck cancer: an examination of 20,915 patients. Cancer. 2008;113(10):2797-2806.

29.

Halpern

Ward

Pavluck

Schrag

Bian

Chen

AY.

Association of insurance status and ethnicity with cancer stage at diagnosis for 12 cancer sites: a retrospective analysis. Lancet Oncol. 2008;9(3):222-231.

30.

Inverso

Mahal

Aizer

Donoff

Chuang

SK.

Health insurance affects head and neck cancer treatment patterns and outcomes. J Oral Maxillofac Surg. 2016;74(6):1241-1247.

31.

Kwok

Langevin

Argiris

Grandis

Gooding

Taioli

The impact of health insurance status on the survival of patients with head and neck cancer. Cancer. 2010;116(2):476-485.

32.

Naghavi

Echevarria

Grass

, et al. Having medicaid insurance negatively impacts outcomes in patients with head and neck malignancies. Cancer. 2016;122(22):3529-3537.

33.

Shin

Yoon

Shin

Blumenfeld

Mai

Diaz

AZ.

Association of insurance and community-level socioeconomic status with treatment and outcome of squamous cell carcinoma of the pharynx. JAMA Otolaryngol Head Neck Surg. 2017;143(9):899-907.

34.

Harris

Taylor

Thielke

Payne

Gonzalez

Conde

JG.

Research electronic data capture (REDCap)–a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381.

35.

Harris

Taylor

Minor

, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95:103208.

36.

Assistant Secretary for Planning and Evaluation. “2021 Poverty Guidelines.” https://aspe.hhs.gov/2021-poverty-guidelines. Accessed June 6, 2022.

37.

Scholz

Gutiérrez Doña

Sud

Schwarzer

Is general self-efficacy a universal construct?1. Eur J Psychol Assess. 2002;18(3):242-251.

38.

Newell

Sanson-Fisher

Savolainen

NJ.

Systematic review of psychological therapies for cancer patients: overview and recommendations for future research. J Natl Cancer Inst. 2002;94(8):558-584.

39.

Stanton

AL.

Psychosocial concerns and interventions for cancer survivors. J Clin Oncol. 2006;24(32):5132-5137.

40.

Riba

Donovan

Andersen

, et al. Distress management, version 3.2019, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2019;17(10):1229-1249.

41.

Graboyes

Kompelli

Neskey

, et al. Association of treatment delays with survival for patients with head and neck cancer: a systematic review. JAMA Otolaryngol Head Neck Surg. 2019;145(2):166-177.

42.

Murphy

Galloway

Handorf

, et al. Survival impact of increasing time to treatment initiation for patients with head and neck cancer in the United States. J Clin Oncol. 2016;34(2):169-178.

43.

Rygalski

Zhao

Eskander

, et al. Time to surgery and survival in head and neck cancer. Ann Surg Oncol. 2021;28(2):877-885.

44.

Windon

D’Souza

Faraji

, et al. Priorities, concerns, and regret among patients with head and neck cancer. Cancer. 2019;125(8):1281-1289.

45.

Fagerlind

Kettis Glimelius

Ring

Barriers against psychosocial communication: oncologists' perceptions. Clin Oncol. 2013;31(30):3815-3822.

46.

Luckett

Davidson

Boyle

, et al. Australian survey of current practice and guideline use in adult cancer pain assessment and management: perspectives of oncologists. Asia Pac J Clin Oncol. 2014;10(2):e99-107.

47.

Berkowitz

Allen

Tenhover

, et al. Knowledge and preferences of primary care providers in delivering head and neck cancer survivorship care. J Cancer Educ. 2018;33(6):1323-1327.

48.

Chen

Hong

, et al. Communication dysfunction, body image, and symptom severity in postoperative head and neck cancer patients: factors associated with the amount of speaking after treatment. Support Care Cancer. 2015;23(8):2375-2382.

49.

Prouty

Mazor

Greene

, et al. Providers' perceptions of communication breakdowns in cancer care. J Gen Intern Med. 2014;29(8):1122-1130.

50.

Warren

Marshall

Cummings

, et al. Addressing tobacco use in patients with cancer: a survey of American society of clinical oncology members. J Oncol Pract. 2013;9(5):258-262.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.26 MB