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Figure.
Flow of Participants Through the Study
Flow of Participants Through the Study

The 10 patients who did not complete the 3-month assessment went on to complete a 12-month assessment that was not relevant to the current study.

Table 1.  
Characteristics of 107 Participants Newly Diagnosed With Uveal Melanoma
Characteristics of 107 Participants Newly Diagnosed With Uveal Melanoma
Table 2.  
Potential Factors Associated With Total Unmet Need Severity 1 Week After Diagnosis of Uveal Melanoma Using a Multivariable Linear Regression Modela
Potential Factors Associated With Total Unmet Need Severity 1 Week After Diagnosis of Uveal Melanoma Using a Multivariable Linear Regression Modela
Table 3.  
Potential Factors Associated With Total Unmet Need Severity 3 Months After Diagnosis of Uveal Melanoma Using a Multivariable Linear Regression Modela
Potential Factors Associated With Total Unmet Need Severity 3 Months After Diagnosis of Uveal Melanoma Using a Multivariable Linear Regression Modela
Table 4.  
Potential Factors Associated With Change in Total Unmet Need Severity From 1 Week After Diagnosis of Uveal Melanoma to 3 Months Later Using a Multivariable Linear Regression Modela
Potential Factors Associated With Change in Total Unmet Need Severity From 1 Week After Diagnosis of Uveal Melanoma to 3 Months Later Using a Multivariable Linear Regression Modela
1.
McLaughlin  CC, Wu  XC, Jemal  A, Martin  HJ, Roche  LM, Chen  VW.  Incidence of noncutaneous melanomas in the U.S.  Cancer. 2005;103(5):1000-1007.PubMedGoogle ScholarCrossref
2.
Singh  AD, Turell  ME, Topham  AK.  Uveal melanoma: trends in incidence, treatment, and survival.  Ophthalmology. 2011;118(9):1881-1885.PubMedGoogle ScholarCrossref
3.
Collaborative Ocular Melanoma Study Group.  Sociodemographic and clinical predictors of participation in two randomized trials: findings from the Collaborative Ocular Melanoma Study COMS report No. 7.  Control Clin Trials. 2001;22(5):526-537.PubMedGoogle ScholarCrossref
4.
Damato  BE, Coupland  SE.  Ocular melanoma.  Saudi J Ophthalmol. 2012;26(2):137-144.PubMedGoogle ScholarCrossref
5.
Seddon  JM, Gragoudas  ES, Polivogianis  L,  et al.  Visual outcome after proton beam irradiation of uveal melanoma.  Ophthalmology. 1986;93(5):666-674.PubMedGoogle ScholarCrossref
6.
Scholes  AGM, Damato  BE, Nunn  J, Hiscott  P, Grierson  I, Field  JK.  Monosomy 3 in uveal melanoma: correlation with clinical and histologic predictors of survival.  Invest Ophthalmol Vis Sci. 2003;44(3):1008-1011.PubMedGoogle ScholarCrossref
7.
Chattopadhyay  C, Kim  DW, Gombos  DS,  et al.  Uveal melanoma: from diagnosis to treatment and the science in between.  Cancer. 2016;122(15):2299-2312.PubMedGoogle ScholarCrossref
8.
Cossich  T, Schofield  P, McLachlan  SA.  Validation of the Cancer Needs Questionnaire (CNQ) short-form version in an ambulatory cancer setting.  Qual Life Res. 2004;13(7):1225-1233.PubMedGoogle ScholarCrossref
9.
Larsson  G, Widmark Peterson  V, Lampic  C, von Essen  L, Sjödén  PO.  Cancer patient and staff ratings of the importance of caring behaviors and their relations to patient anxiety and depression.  J Adv Nurs. 1998;27(4):855-864.PubMedGoogle ScholarCrossref
10.
Snyder  CF, Dy  SM, Hendricks  DE,  et al.  Asking the right questions: investigating needs assessments and health-related quality-of-life questionnaires for use in oncology clinical practice.  Support Care Cancer. 2007;15(9):1075-1085.PubMedGoogle ScholarCrossref
11.
Walker  MS, Ristvedt  SL, Haughey  BH.  Patient care in multidisciplinary cancer clinics: does attention to psychosocial needs predict patient satisfaction?  Psychooncology. 2003;12(3):291-300.PubMedGoogle ScholarCrossref
12.
Cella  D, Stone  AA.  Health-related quality of life measurement in oncology: advances and opportunities.  Am Psychol. 2015;70(2):175-185.PubMedGoogle ScholarCrossref
13.
Selby  JV, Beal  AC, Frank  L.  The Patient-Centered Outcomes Research Institute (PCORI) national priorities for research and initial research agenda.  JAMA. 2012;307(15):1583-1584.PubMedGoogle ScholarCrossref
14.
Brandberg  Y, Kock  E, Oskar  K, af Trampe  E, Seregard  S.  Psychological reactions and quality of life in patients with posterior uveal melanoma treated with ruthenium plaque therapy or enucleation: a one year follow-up study.  Eye (Lond). 2000;14(pt 6):839-846.PubMedGoogle ScholarCrossref
15.
Wiley  JF, Laird  K, Beran  T, McCannel  TA, Stanton  AL.  Quality of life and cancer-related needs in patients with choroidal melanoma.  Br J Ophthalmol. 2013;97(11):1471-1474.PubMedGoogle ScholarCrossref
16.
Fiszer  C, Dolbeault  S, Sultan  S, Brédart  A.  Prevalence, intensity, and predictors of the supportive care needs of women diagnosed with breast cancer: a systematic review.  Psychooncology. 2014;23(4):361-374.PubMedGoogle ScholarCrossref
17.
Soothill  K, Morris  SM, Harman  J, Francis  B, Thomas  C, McIllmurray  MB.  The significant unmet needs of cancer patients: probing psychosocial concerns.  Support Care Cancer. 2001;9(8):597-605.PubMedGoogle ScholarCrossref
18.
Barg  FK, Cronholm  PF, Straton  JB,  et al.  Unmet psychosocial needs of Pennsylvanians with cancer: 1986-2005.  Cancer. 2007;110(3):631-639.PubMedGoogle ScholarCrossref
19.
Moadel  AB, Morgan  C, Dutcher  J.  Psychosocial needs assessment among an underserved, ethnically diverse cancer patient population.  Cancer. 2007;109(2)(suppl):446-454.PubMedGoogle ScholarCrossref
20.
Sanson-Fisher  R, Girgis  A, Boyes  A, Bonevski  B, Burton  L, Cook  P; Supportive Care Review Group.  The unmet supportive care needs of patients with cancer.  Cancer. 2000;88(1):226-237.PubMedGoogle ScholarCrossref
21.
John  DA, Kawachi  I, Lathan  CS, Ayanian  JZ.  Disparities in perceived unmet need for supportive services among patients with lung cancer in the Cancer Care Outcomes Research and Surveillance Consortium.  Cancer. 2014;120(20):3178-3191.PubMedGoogle ScholarCrossref
22.
Hope-Stone  L, Brown  SL, Heimann  H, Damato  B, Salmon  P.  Two-year patient-reported outcomes following treatment of uveal melanoma.  Eye (Lond). 2016;30(12):1598-1605.PubMedGoogle ScholarCrossref
23.
Uchino  BN.  Social support and health: a review of physiological processes potentially underlying links to disease outcomes.  J Behav Med. 2006;29(4):377-387.PubMedGoogle ScholarCrossref
24.
Digman  J.  Personality structure: Emergence of the five-factor model.  Annu Rev Psychol. 1990;41(1):417-440.Google ScholarCrossref
25.
de Ridder  D, Geenen  R, Kuijer  R, van Middendorp  H.  Psychological adjustment to chronic disease.  Lancet. 2008;372(9634):246-255.PubMedGoogle ScholarCrossref
26.
Holladay  JT.  Visual acuity measurements.  J Cataract Refract Surg. 2004;30(2):287-290.PubMedGoogle ScholarCrossref
27.
Sherbourne  CD, Hays  RD, Ordway  L, DiMatteo  MR, Kravitz  RL.  Antecedents of adherence to medical recommendations: results from the Medical Outcomes Study.  J Behav Med. 1992;15(5):447-468.PubMedGoogle ScholarCrossref
28.
Rowland  JH, Desmond  KA, Meyerowitz  BE, Belin  TR, Wyatt  GE, Ganz  PA.  Role of breast reconstructive surgery in physical and emotional outcomes among breast cancer survivors.  J Natl Cancer Inst. 2000;92(17):1422-1429.PubMedGoogle ScholarCrossref
29.
Kemeny  NE, Niedzwiecki  D, Hollis  DR,  et al.  Hepatic arterial infusion versus systemic therapy for hepatic metastases from colorectal cancer: a randomized trial of efficacy, quality of life, and molecular markers (CALGB 9481).  J Clin Oncol. 2006;24(9):1395-1403.PubMedGoogle ScholarCrossref
30.
Costa  PT, McCrae  RR.  NEO Personality Inventory-Revised (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) Professional Manual. Odessa, FL: Psychological Assessment Resources; 1992.
31.
Dar-Nimrod  I, Chapman  BP, Franks  P,  et al.  Personality factors moderate the associations between apolipoprotein genotype and cognitive function as well as late onset Alzheimer disease.  Am J Geriatr Psychiatry. 2012;20(12):1026-1035.PubMedGoogle ScholarCrossref
32.
Asghari  A, Nicholas  MK.  Pain self-efficacy beliefs and pain behaviour: a prospective study.  Pain. 2001;94(1):85-100.PubMedGoogle ScholarCrossref
33.
Foot  G, Sanson-Fisher  R.  Measuring the unmet needs of people living with cancer.  Cancer Forum. 1995;19(2):131-135.Google Scholar
34.
Aranda  S, Schofield  P, Weih  L,  et al.  Mapping the quality of life and unmet needs of urban women with metastatic breast cancer.  Eur J Cancer Care (Engl). 2005;14(3):211-222.PubMedGoogle ScholarCrossref
35.
Chen  S-C, Liao  C-T, Lin  C-C, Chang  JT-C, Lai  Y-H.  Distress and care needs in newly diagnosed oral cavity cancer patients receiving surgery.  Oral Oncol. 2009;45(9):815-820.PubMedGoogle ScholarCrossref
36.
Hetz  SP, Tomasone  JR.  Supportive care needs of Canadian melanoma patients and survivors.  Can Oncol Nurs J. 2012;22(4):248-256.PubMedGoogle ScholarCrossref
37.
Smith  DP, Supramaniam  R, King  MT, Ward  J, Berry  M, Armstrong  BK.  Age, health, and education determine supportive care needs of men younger than 70 years with prostate cancer.  J Clin Oncol. 2007;25(18):2560-2566.PubMedGoogle ScholarCrossref
38.
Harrison  SE, Watson  EK, Ward  AM,  et al.  Primary health and supportive care needs of long-term cancer survivors: a questionnaire survey.  J Clin Oncol. 2011;29(15):2091-2098.PubMedGoogle ScholarCrossref
39.
Lam  WWT, Au  AHY, Wong  JHF,  et al.  Unmet supportive care needs: a cross-cultural comparison between Hong Kong Chinese and German Caucasian women with breast cancer.  Breast Cancer Res Treat. 2011;130(2):531-541.PubMedGoogle ScholarCrossref
40.
Hovén  E, Lannering  B, Gustafsson  G, Boman  KK.  The met and unmet health care needs of adult survivors of childhood central nervous system tumors: a double-informant, population-based study.  Cancer. 2011;117(18):4294-4303.PubMedGoogle ScholarCrossref
41.
Graham  JW.  Missing data analysis: making it work in the real world.  Annu Rev Psychol. 2009;60:549-576.PubMedGoogle ScholarCrossref
42.
Enders  C, Bandalos  D. The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Struct Equ Model A Multidiscip J. 2001;8(3):430–57.
43.
Minstrell  M, Winzenberg  T, Rankin  N, Hughes  C, Walker  J.  Supportive care of rural women with breast cancer in Tasmania, Australia: changing needs over time.  Psychooncology. 2008;17(1):58-65.PubMedGoogle ScholarCrossref
44.
Sutherland  G, Hill  D, Morand  M, Pruden  M, McLachlan  SA.  Assessing the unmet supportive care needs of newly diagnosed patients with cancer.  Eur J Cancer Care (Engl). 2009;18(6):577-584.PubMedGoogle ScholarCrossref
45.
McDowell  ME, Occhipinti  S, Ferguson  M, Dunn  J, Chambers  SK.  Predictors of change in unmet supportive care needs in cancer.  Psychooncology. 2010;19(5):508-516.PubMedGoogle ScholarCrossref
46.
Armes  J, Crowe  M, Colbourne  L,  et al.  Patients’ supportive care needs beyond the end of cancer treatment: a prospective, longitudinal survey.  J Clin Oncol. 2009;27(36):6172-6179.PubMedGoogle ScholarCrossref
47.
Collaborative Ocular Melanoma Study–Quality of Life Study Group.  Quality of life after iodine 125 brachytherapy vs enucleation for choroidal melanoma: 5-year results from the Collaborative Ocular Melanoma Study: COMS-QOLS report No. 3.  Arch Ophthalmol. 2006;124:226-238.PubMedGoogle ScholarCrossref
48.
Beesley  V, Eakin  E, Steginga  S, Aitken  J, Dunn  J, Battistutta  D.  Unmet needs of gynaecological cancer survivors: implications for developing community support services.  Psychooncology. 2008;17(4):392-400.PubMedGoogle ScholarCrossref
49.
Sherbourne  CD, Stewart  AL.  The MOS social support survey.  Soc Sci Med. 1991;32(6):705-714.PubMedGoogle ScholarCrossref
50.
Taylor  SE. Social support: a review. In: Friedman  HS, ed.  The Oxford Handbook of Health Psychology. New York, NY: Oxford University Press; 2011:189-214.
51.
Brissette  I, Cohen  S, Seeman  TE. Measuring social integration and social networks. In: Social Support Measurement and Intervention: A Guide for Health and Social Scientists. New York, NY: Oxford University Press; 2000:53-85.
52.
Carlson  LE, Waller  A, Mitchell  AJ.  Screening for distress and unmet needs in patients with cancer: review and recommendations.  J Clin Oncol. 2012;30(11):1160-1177.PubMedGoogle ScholarCrossref
53.
Butow  PN, Bell  ML, Smith  AB,  et al; Conquer Fear Authorship Group.  Conquer fear: protocol of a randomised controlled trial of a psychological intervention to reduce fear of cancer recurrence.  BMC Cancer. 2013;13(1):201.PubMedGoogle ScholarCrossref
54.
Fawzy  FI, Fawzy  NW.  A structured psychoeducational intervention for cancer patients.  Gen Hosp Psychiatry. 1994;16(3):149-192.PubMedGoogle ScholarCrossref
55.
Boesen  EH, Ross  L, Frederiksen  K,  et al.  Psychoeducational intervention for patients with cutaneous malignant melanoma: a replication study.  J Clin Oncol. 2005;23(6):1270-1277.PubMedGoogle ScholarCrossref
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Original Investigation
April 2018

Sociodemographic, Medical, and Psychosocial Factors Associated With Supportive Care Needs in Adults Diagnosed With Uveal Melanoma

Author Affiliations
  • 1Department of Psychology, University of California, Los Angeles
  • 2Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
  • 3Department of Ophthalmology, Stein and Doheny Eye Institutes, University of California, Los Angeles
  • 4Jonsson Comprehensive Cancer Center, University of California, Los Angeles
  • 5Cousins Center of Psychoneuroimmunology, Semel Institute, University of California, Los Angeles
JAMA Ophthalmol. 2018;136(4):356-363. doi:10.1001/jamaophthalmol.2018.0019
Key Points

Question  What are the needs of patients with newly diagnosed uveal melanoma, and what sociodemographic, medical, and psychosocial factors assessed prior to cancer diagnosis are associated with unmet need severity after diagnosis among this patient group?

Findings  This survey study demonstrated that nearly all patients endorsed at least 1 unmet need at 1 week after diagnosis, and while need severity decreased within 3 months, most patients continued to report important unmet needs. Neuroticism, instrumental social support, and social network size as assessed before diagnosis were associated with unmet need severity more than sociodemographic and medical characteristics.

Meaning  Social support and neuroticism prior to diagnosis could be assessed to identify patients for proactive supportive intervention.

Abstract

Importance  Understanding supportive care needs in patients with cancer is important for developing approaches that enhance quality of life and promote satisfaction with care.

Objective  To characterize the nature and frequency of sociodemographic, medical, and psychosocial factors associated with unmet needs in patients with uveal melanoma 1 week and 3 months after diagnosis.

Design, Setting, and Participants  This 3-month, prospective, longitudinal survey study was conducted at a university-based ophthalmology practice from June 1, 2007, to July 1, 2011. Data were analyzed in April 2017. Consecutive patients (n = 429) scheduled for diagnostic evaluation for an intraocular abnormality were assessed for eligibility. Participants were ineligible (n = 25) if they were younger than 18 years, had previous advanced cancer, or evidenced cognitive impairment. Of the patients who provided informed consent (n = 306), those subsequently diagnosed with uveal melanoma by an ophthalmologist (n = 107) were included in the analysis.

Main Outcomes and Measures  Unmet needs (ie, desire for help in psychological, physical, health information, communication, or social domains) were assessed using the Cancer Needs Questionnaire. Multivariable regression analyses determined factors associated with unmet need severity across 3 months.

Results  One hundred seven patients (58 [54%] men; mean [SD] age, 59.0 [12.8] years) completed the baseline assessment. At 1 week after diagnosis, nearly all patients (85 of 86 [99%]) expressed at least 1 unmet need, as did 68 of 79 (86%) 3 months later. The most frequently endorsed needs were in the health information and psychological domains. Patients’ unmet needs declined significantly over 3 months (mean [SD] change, −10.0 [14.4]; 95% CI, −6.4 to −13.6; t = −5.6). Sociodemographic and medical characteristics were unrelated to unmet need severity. However, higher prediagnosis instrumental social support (b = −0.2; 95% CI, −0.3 to −0.1; z = −2.8) and lower neuroticism (b = 0.3; 95% CI, 0.1-0.5; z = 2.9) predicted lower unmet need severity 1 week after diagnosis. Having a smaller social network predicted lower unmet need severity 3 months after diagnosis (b < 0.1; 95% CI, <0.1 to <0.1; z = 2.4) as well as a decline in needs from diagnosis to 3 months later (b < 0.1; 95% CI, <0.1 to <0.1; z = 2.3).

Conclusions and Relevance  Within 1 week after diagnosis and 3 months later, most patients with uveal melanoma cited important health information and psychological needs. These findings suggest that prior to or at diagnosis, the severity of such needs and psychosocial factors that may be associated can be identified for proactive supportive intervention.

Introduction

Uveal melanoma is the most common primary intraocular cancer in adults, affecting 4 to 7 adults per million per year in the United States.1,2 Treatments include local brachytherapy, proton beam radiotherapy, and, when the tumor is large, enucleation.3,4 Radiotherapy causes vision impairment, which can also result from tissue disruption from the melanoma or enucleation.5 A substantial proportion of patients with uveal melanoma develop metastatic disease to the liver,4,6 which currently has few effective preventive or therapeutic options.7 Clinical experience suggests that patients newly diagnosed with uveal melanoma often have not heard of eye cancer, fear vision loss, and express concerns about mortality.

Supportive care needs involve the desire for help in psychological, physical, health information, communication, or social domains.8 Identifying patients’ needs is important, given that patients’ and oncologists’ reports of health care needs are often incongruent.9,10 Also, addressing patients’ supportive care needs is associated with better quality of life and satisfaction with care.11 Although patient-reported outcomes are used increasingly in oncology,12,13 the needs of patients with uveal melanoma are relatively unknown.

Most patients with uveal melanoma retrospectively report reduced quality of life following diagnosis, and a substantial minority have clinical levels of depression and anxiety within the first year of diagnosis.14 A prior cross-sectional study15 assessed supportive care needs among patients with uveal melanoma. Patients reported low levels of unmet needs, but they were recruited 2 years after diagnosis on average.15 More unmet needs were related to lower quality of life, more depressive symptoms, and higher fear of recurrence.15 Research is needed to characterize the supportive care needs of patients with uveal melanoma early in the cancer trajectory.

Identifying the factors associated with unmet needs can promote early identification of patients with cancer who could benefit from supportive care. In other cancers, correlational findings indicate that more recent diagnosis is associated with more unmet needs,16 as are sociodemographic characteristics (eg, younger age, female sex, unmarried status).17-21 Additionally, younger age and female sex are associated with more anxiety in patients with uveal melanoma.22 Psychosocial attributes are understudied as factors associated with needs. Higher perceived support helps buffer against the negative effects of stress on health,23 and research is needed to evaluate the relationship between support and unmet needs. Additionally, neuroticism (ie, tendency to experience anxiety, worry, and fear)24 is associated with poor disease-related adjustment,25 but its association with supportive care needs is unknown. In this study, we describe a prospective, longitudinal investigation of supportive care needs and their associated factors in a university practice of patients with uveal melanoma recruited prior to diagnostic evaluation. To our knowledge, no study in uveal melanoma has involved prospective and longitudinal assessment of supportive care needs and their associated factors. We aimed to characterize types of unmet needs and describe their frequency as well as related sociodemographic, medical, and prediagnosis psychosocial factors 1 week after diagnosis and 3 months later.

Methods
Patients and Procedures

Recruited by research staff between June 1, 2007 and July 1, 2011, patients were eligible if they were (1) scheduled to receive diagnostic evaluation for an intraocular abnormality at the University of California, Los Angeles, Stein Eye Institute and (2) able to respond to questionnaires in English. Participants were ineligible if they (1) were younger than 18 years, (2) had previously been diagnosed with advanced cancer, or (3) had observable cognitive impairment. Eligible patients completed a self-report questionnaire at baseline, which occurred immediately before the diagnostic evaluation, 1 week after the diagnosis was communicated to the participant, and 3 months later. To reduce bias, consecutive patients were recruited.

Power analysis revealed that a sample size of 120 participants would provide 80% power to detect as significant (P < .05) a moderate effect size. The Figure outlines participant (n = 306) flow. Current analyses included patients subsequently diagnosed with uveal melanoma (n = 107), the subsample attained when funding ended. All procedures were approved by the institutional review board at the University of California, Los Angeles. Patients provided written informed consent.

Measures

At baseline, patients reported age, sex (male or female), race (non-Hispanic white or other ethnicity/race), years of education, employment status (unemployed or currently employed), family income, marital status (unmarried or married), number of years married, and number of children. Number of medical comorbidities, family cancer history (no or yes), prior nonuveal melanoma cancer diagnosis (no or yes), cytogenetic testing result (ie, an indicator of risk for metastasis; normal signaling or anomalous signaling), and visual acuity of the participant were assessed via medical record review. Visual acuity at baseline was computed as the logMAR following established guidelines.26 Treatment type was not included as a factor; 105 of 107 patients (98%) received radioactive plaque, and findings were identical when the 2 patients who underwent enucleation were excluded from analyses.

Perceived availability of social support was assessed at baseline using the 20-item Medical Outcomes Study Social Support Survey,27 which has excellent psychometric properties27 and has been used in patients with cancer.28,29 Participants indicated the number of close friends and relatives (ie, social network size), availability of instrumental support (eg, “Someone to take you to the doctor if you needed it”), and availability of emotional, positive interaction, or affectionate support (eg, “Someone to love and make you feel wanted”). These items were combined and hereafter are labeled emotional support because the subscales were highly correlated (r > 0.7; P < .001). Social network size, instrumental support, and emotional support were correlated significantly (r = 0.2-0.7; P < .05).

Neuroticism was assessed at baseline using the 12-item subscale of the NEO Revised Five Factor Inventory.30 Participants responded to items (eg, “I often feel tense and jittery”) on a 5-point Likert scale. Internal consistency is high in patient samples.31,32

Quiz Ref IDAt the 1-week and 3-month assessments, participants completed the 32-item Cancer Needs Questionnaire–Short Form (CNQ),8,33 which has been used in populations of patients with cancer,34-36 including patients with uveal melanoma15 (current α = .94-.96). The CNQ assesses 5 domains of supportive care needs: health information (eg, “to be fully informed about the odds of treatment success”), psychological (eg, “coping with an uncertain future”), patient care and support (eg, “to be reassured by medical staff that your physical and emotional responses are normal”), interpersonal communication (eg, “coping with awkwardness in talking with others about the cancer”), and physical and daily living (eg, “coping with disturbed sleep”). Respondents indicated on a 5-point Likert scale whether they had no need (1 = not applicable, 2 = already satisfied) or some level of need (3 = low need, 4 = moderate need, 5 = high need) for each item. The CNQ was scored 3 ways. First, responses of not applicable or already met were grouped as no unmet need (score = 0), and the other responses were grouped as at least 1 unmet need (score = 1).37-39 Second, consistent with CNQ scoring guidelines,8 each item was rescored such that scores ranged from 0 to 100. Third, although logistic regression typically is used to evaluate predictors of dichotomous unmet needs,20,37 it does not adequately capture the severity of needs. Therefore, a novel scoring approach was used for predictive analyses on unmet need severity as a continuous outcome. Responses of not applicable or already met were grouped as no unmet need (score = 0), low need (score = 1), moderate need (score = 2), and high need (score = 3).

Statistical Analysis

The proportion of patients who reported at least 1 unmet need within each domain was computed. Frequencies of individual items were examined to identify commonly reported needs. Differences between 1-week and 3-month supportive care needs were evaluated with paired-sample t tests, and Pearson product-moment correlations indicated associations between domains. Relationships of needs with sociodemographic and medical characteristics were tested with correlations or t tests.

Multivariable regression models using the SEM command in Stata release 13 statistical software (StataCorp LLC) evaluated neuroticism and social support as predictors of 1-week and 3-month unmet need severity. To assess change, 1-week unmet need severity was entered into the analysis as a covariate and the 3-month score was entered as the outcome. Statistical assumptions were satisfied for all analyses. Two-tailed significance tests were used, and P < .05 was considered statistically significant. A priori based on evidence,20,21,40 age, sex, education, and number of medical comorbidities were selected as covariates. As per an a priori decision, any other patient characteristic associated with the outcome at P < .10 was added as a covariate. Likelihood ratio tests were conducted between the covariate-only and full models to assess whether the addition of psychosocial factors produced a better model fit. Regression models were estimated with full information maximum likelihood to address missing data,41,42 which ranged from 0% to 26%.

Results
Study Participants

A total of 429 patients were screened and 25 were ineligible. Of the patients who provided informed consent (n = 306), those subsequently diagnosed with uveal melanoma (n = 107) were included in the analysis. Participants were men (n = 58) and women (n = 49) diagnosed with uveal melanoma after undergoing clinical evaluation. All participants were free of clinically detectable metastasis. Participants had a mean (SD) age of 59.0 (12.8) years, a mean (SD) of 15.2 (3.1) years of education, and on average were partnered (74 [69%] married or living as married), non-Hispanic white (96 [90%]), and had at least 1 comorbidity (mean [SD], 1.5 [1.3] comorbidities) (Table 1).

Frequency of Supportive Care Needs

Quiz Ref IDAt 1 week after diagnosis, nearly all patients (85 of 86 [99%]) reported at least 1 unmet need, as did 68 of 79 (86%) 3 months later. The proportions who reported at least 1 unmet need at 1 week and 3 months, respectively, in each domain were 93% (n = 77 of 83) and 69% (n = 53 of 77) for psychological, 92% (n = 79 of 86) and 77% (n = 60 of 78) for health information, 70% (n = 57 of 81) and 52% (n = 40 of 77) for patient care and support, 67% (n = 57 of 85) and 54% (n = 43 of 79) for physical and daily living, and 49% (n = 42 of 85) and 23% (n = 18 of 78) for interpersonal communication. Of the 10 most frequently endorsed supportive care needs, 7 were in the health information domain and 3 were in the psychological domain (eTable in the Supplement).

Correlations among domains were r = 0.2 to 0.7. Total unmet needs declined from 1 week after diagnosis (mean [SD], 46.2 [16.9]) to 3 months later (mean [SD], 35.9 [20.7]) (mean [SD] change, −10.0 [14.4]; 95% CI, −6.4 to −13.6; t64 = −5.6; P < .001), as they did in each domain (t > 3.1; P < .003), except for physical and daily living needs (t64 = −0.4; P = .71).

Evaluation of Potential Factors Associated With Supportive Care Needs
Sociodemographic and Medical Characteristics

Quiz Ref IDNo sociodemographic or medical characteristic was associated significantly with 1-week or 3-month total unmet need severity: age, education, family income, years married, number of children, number of medical comorbidities, and visual acuity. Additionally, unmet need severity did not differ significantly by sex, race/ethnicity, employment, marital status, family cancer history, prior nonuveal melanoma cancer diagnosis, or cytogenetic testing result.

Psychosocial Factors

Baseline social support and neuroticism were tested as factors associated with 1-week unmet need severity, controlling for a priori covariates (Table 2). The covariates were not significant factors. Higher instrumental support (b = −0.2; 95% CI, −0.3 to −0.1; z = −2.8) and lower neuroticism (b = 0.3; 95% CI, 0.1-0.5; z = 2.9) at baseline were associated with lower 1-week unmet need severity. Social network size and emotional support were not significantly related to need severity. The model with neuroticism and social support variables produced a better model fit than the covariate-only model (χ24 = 20.7; P < .001).

The covariates were not significantly associated with 3-month unmet need severity (Table 3). However, higher levels of instrumental support (b = −0.2; 95% CI, −0.4 to <−0.1; z = −2.4) and smaller social network size (b < 0.1; 95% CI, <0.1 to <0.1; z = 2.4) at baseline was associated with lower 3-month unmet need severity. Emotional support and neuroticism were not significant factors. The model with psychosocial factors produced a better model fit than the covariate-only model (χ24 = 17.0; P = .002).

Finally, we evaluated baseline social support and neuroticism as factors associated with 3-month unmet need severity, controlling for 1-week need severity (Table 4). One-week severity of unmet needs (b = 0.7; 95% CI, 0.6-0.9; z = 8.2) was the factor most strongly associated with 3-month unmet need severity. Additionally, smaller social network size (b = <0.1; 95% CI, <0.1 to <0.1; z = 2.3) at baseline was significantly associated with lower 3-month unmet need severity, adjusted for the 1-week value. Neither the sociodemographic and medical covariates nor the other psychosocial factors were significantly associated with unmet needs. The model with psychosocial factors produced a marginally better model fit than the covariate-only model (χ24 = 8.4; P = .08).

Post Hoc Analyses

Exploratory independent-sample t tests compared findings with an earlier study at the same institution with a sample (n = 99; median age = 65 years) of patients with uveal melanoma (51 men, 48 women) on average more than 2 years after diagnosis.15 Total unmet needs (scored 0-100) were higher in the current sample 1 week after diagnosis (t178 = 4.7; P < .001), but not 3 months later (t171 = 0.9; P = .39).

Discussion

We aimed to characterize the nature and severity of supportive care needs and associated psychosocial factors in patients with uveal melanoma at 1 week and 3 months after diagnosis. Nearly all patients (85 of 86 [99%]) endorsed at least 1 unmet need at 1 week after initial presentation, as did 68 of 79 (86%) 3 months later. These proportions are higher than those observed in samples of patients with newly diagnosed breast,43 prostate,37 and other44 cancers. The particularly high needs of patients with newly diagnosed uveal melanoma might result from the disease’s short diagnosis and treatment trajectory and its rarity. Research is needed to evaluate whether the rapidity of the process is disconcerting for some patients, even though they typically receive treatment that is less burdensome than chemotherapy or more prolonged radiation. Compared with other samples of patients with cancer,20,38,45 the present sample reported more health information needs (eg, “to be fully informed about cancer remission”) among the 10 most frequently reported needs. The disease’s rarity likely prompts patients’ desire for information about treatment and prognosis. Also, the term remission may not frequently be used by medical professionals when counseling patients with uveal melanoma, and patients may benefit from receiving information about the nature of remission in the context of the disease.

Quiz Ref IDFindings correspond to research indicating that needs are most prominent at the time of diagnosis.16 Unmet needs were high 1 week after diagnosis and declined significantly across 3 months to levels comparable to those of patients with uveal melanoma who averaged 2 years after diagnosis.15 (The stability of physical and daily living needs may reflect ongoing problems that began before diagnosis.) Six months after treatment, quality of life in patients with uveal melanoma appears similar to that in the general population.22 Unmet needs, however, were still endorsed by most patients 3 months after diagnosis. Therefore, it is important to consider the long-term effects of uveal melanoma, given that supportive care is indicated beyond treatment completion in other groups of patients with cancer.46

Unmet need severity was unrelated to sociodemographic and medical factors, which is somewhat inconsistent with previous research suggesting that greater unmet needs in patients with other types of cancer are associated with younger age,17,18 female sex,20 unmarried status,21 and African American race or Hispanic ethnicity (vs non-Hispanic white).19 Lower neuroticism and higher perceived instrumental support prior to diagnostic evaluation were associated with lower unmet need severity 1 week after diagnosis, with sociodemographic and medical characteristics controlled. Smaller social network size before diagnosis was associated with lower unmet need severity 3 months after diagnosis as well as a decline in needs across 3 months. Following a uveal melanoma diagnosis, patients high in neuroticism are likely to experience anxiety, which is important to address given that patients undergoing brachytherapy who have anxiety are less likely to experience decreases in anxiety over time than patients who have undergone enucleation.47

Patients with cancer who have strong social support are theorized to have fewer unmet needs.17 However, in 2 studies, a composite index of social support was unrelated to needs.45,48 The present findings suggest the importance of evaluating instrumental and emotional support as separate constructs, in that higher perceived instrumental (but not emotional) support at baseline significantly predicted lower unmet need severity 1 week after diagnosis. Instrumental support may be important for patients with uveal melanoma because vision impairment often accompanies treatment. Patients may benefit from knowing they have transportation to appointments with physicians, for example, which is assessed in the subscale.49

Having a smaller social network was associated with lower 3-month unmet need severity as well as a decline in unmet needs across 3 months. This surprising finding may result from members of large and interactive social networks offering overwhelming or conflicting advice during stressful life events.50 Perhaps smaller social networks can provide coordinated or higher-quality support that is well suited to patients’ needs. Future studies should assess the nature and frequency of contact within one’s network.51

Pending replication of the present findings, supportive care needs assessment can promote early identification of patients with uveal melanoma who need support. It is important for health professionals to proactively screen and address the needs of patients with cancer .52 The medical team can include a mental health professional to target psychological needs, and patients with uveal melanoma may benefit from evidence-based psychological intervention to reduce fear of cancer recurrence.53 Additionally, effective psychoeducational interventions for patients with melanoma54,55 can be tailored for patients with uveal melanoma to address health information and psychological needs.

Limitations

An important strength of the study is that recruitment occurred before cancer diagnosis, which strengthens causal inference that prediagnosis psychosocial factors are associated with supportive care needs after diagnosis and treatment. Particularly in light of the disease’s rarity, the sample size was relatively large, although the small number of patients who had undergone enucleation precluded evaluation of oncologic treatment as a factor. Additionally, patients willing to take part in the study might have been more (or less) willing to report their unmet needs than study refusers. The participation rate was relatively high (76%), however, and attrition across 3 months was low (14%). Finally, participants were predominantly non-Hispanic white. Although the sociodemographic characteristics of the sample are consistent with those of the patient population, caution is warranted in generalizing the findings.

Conclusions

Future research should test interventions that target health information and psychological needs, particularly for those high in neuroticism. Approaches to address needs for instrumental support (eg, transportation to medical appointments) also may confer benefit. Patients could benefit from ongoing support, which in turn could enhance quality of life.

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Article Information

Accepted for Publication: January 1, 2018.

Corresponding Author: Annette L. Stanton, PhD, Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, PO Box 951563, Los Angeles, CA 90095-1563 (astanton@ucla.edu).

Published Online: February 22, 2018. doi:10.1001/jamaophthalmol.2018.0019

Author Contributions: Mr Williamson and Dr Stanton had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Williamson, Jorge-Miller, McCannel, Beran, Stanton.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Williamson.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Williamson.

Obtained funding: Williamson, Beran.

Administrative, technical, or material support: McCannel, Beran, Stanton.

Study supervision: McCannel, Beran, Stanton.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: This work was supported by a National Institute of Mental Health Predoctoral Fellowship (MH 15750; Mr Williamson), the Jonsson Comprehensive Cancer Center Foundation (Drs Beran and Stanton), George E. and Ruth Moss Trust (Dr McCannel), and an unrestricted grant from Research to Prevent Blindness (Dr McCannel).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the authors’ responsibility and does not necessarily represent official views of the National Institutes of Health.

Meeting Presentation: This article was presented in part at the 36th Society of Behavioral Medicine Annual Scientific Meeting; April 25, 2015; San Antonio, Texas.

Additional Contributions: We are grateful to the men and women who took part in this research.

References
1.
McLaughlin  CC, Wu  XC, Jemal  A, Martin  HJ, Roche  LM, Chen  VW.  Incidence of noncutaneous melanomas in the U.S.  Cancer. 2005;103(5):1000-1007.PubMedGoogle ScholarCrossref
2.
Singh  AD, Turell  ME, Topham  AK.  Uveal melanoma: trends in incidence, treatment, and survival.  Ophthalmology. 2011;118(9):1881-1885.PubMedGoogle ScholarCrossref
3.
Collaborative Ocular Melanoma Study Group.  Sociodemographic and clinical predictors of participation in two randomized trials: findings from the Collaborative Ocular Melanoma Study COMS report No. 7.  Control Clin Trials. 2001;22(5):526-537.PubMedGoogle ScholarCrossref
4.
Damato  BE, Coupland  SE.  Ocular melanoma.  Saudi J Ophthalmol. 2012;26(2):137-144.PubMedGoogle ScholarCrossref
5.
Seddon  JM, Gragoudas  ES, Polivogianis  L,  et al.  Visual outcome after proton beam irradiation of uveal melanoma.  Ophthalmology. 1986;93(5):666-674.PubMedGoogle ScholarCrossref
6.
Scholes  AGM, Damato  BE, Nunn  J, Hiscott  P, Grierson  I, Field  JK.  Monosomy 3 in uveal melanoma: correlation with clinical and histologic predictors of survival.  Invest Ophthalmol Vis Sci. 2003;44(3):1008-1011.PubMedGoogle ScholarCrossref
7.
Chattopadhyay  C, Kim  DW, Gombos  DS,  et al.  Uveal melanoma: from diagnosis to treatment and the science in between.  Cancer. 2016;122(15):2299-2312.PubMedGoogle ScholarCrossref
8.
Cossich  T, Schofield  P, McLachlan  SA.  Validation of the Cancer Needs Questionnaire (CNQ) short-form version in an ambulatory cancer setting.  Qual Life Res. 2004;13(7):1225-1233.PubMedGoogle ScholarCrossref
9.
Larsson  G, Widmark Peterson  V, Lampic  C, von Essen  L, Sjödén  PO.  Cancer patient and staff ratings of the importance of caring behaviors and their relations to patient anxiety and depression.  J Adv Nurs. 1998;27(4):855-864.PubMedGoogle ScholarCrossref
10.
Snyder  CF, Dy  SM, Hendricks  DE,  et al.  Asking the right questions: investigating needs assessments and health-related quality-of-life questionnaires for use in oncology clinical practice.  Support Care Cancer. 2007;15(9):1075-1085.PubMedGoogle ScholarCrossref
11.
Walker  MS, Ristvedt  SL, Haughey  BH.  Patient care in multidisciplinary cancer clinics: does attention to psychosocial needs predict patient satisfaction?  Psychooncology. 2003;12(3):291-300.PubMedGoogle ScholarCrossref
12.
Cella  D, Stone  AA.  Health-related quality of life measurement in oncology: advances and opportunities.  Am Psychol. 2015;70(2):175-185.PubMedGoogle ScholarCrossref
13.
Selby  JV, Beal  AC, Frank  L.  The Patient-Centered Outcomes Research Institute (PCORI) national priorities for research and initial research agenda.  JAMA. 2012;307(15):1583-1584.PubMedGoogle ScholarCrossref
14.
Brandberg  Y, Kock  E, Oskar  K, af Trampe  E, Seregard  S.  Psychological reactions and quality of life in patients with posterior uveal melanoma treated with ruthenium plaque therapy or enucleation: a one year follow-up study.  Eye (Lond). 2000;14(pt 6):839-846.PubMedGoogle ScholarCrossref
15.
Wiley  JF, Laird  K, Beran  T, McCannel  TA, Stanton  AL.  Quality of life and cancer-related needs in patients with choroidal melanoma.  Br J Ophthalmol. 2013;97(11):1471-1474.PubMedGoogle ScholarCrossref
16.
Fiszer  C, Dolbeault  S, Sultan  S, Brédart  A.  Prevalence, intensity, and predictors of the supportive care needs of women diagnosed with breast cancer: a systematic review.  Psychooncology. 2014;23(4):361-374.PubMedGoogle ScholarCrossref
17.
Soothill  K, Morris  SM, Harman  J, Francis  B, Thomas  C, McIllmurray  MB.  The significant unmet needs of cancer patients: probing psychosocial concerns.  Support Care Cancer. 2001;9(8):597-605.PubMedGoogle ScholarCrossref
18.
Barg  FK, Cronholm  PF, Straton  JB,  et al.  Unmet psychosocial needs of Pennsylvanians with cancer: 1986-2005.  Cancer. 2007;110(3):631-639.PubMedGoogle ScholarCrossref
19.
Moadel  AB, Morgan  C, Dutcher  J.  Psychosocial needs assessment among an underserved, ethnically diverse cancer patient population.  Cancer. 2007;109(2)(suppl):446-454.PubMedGoogle ScholarCrossref
20.
Sanson-Fisher  R, Girgis  A, Boyes  A, Bonevski  B, Burton  L, Cook  P; Supportive Care Review Group.  The unmet supportive care needs of patients with cancer.  Cancer. 2000;88(1):226-237.PubMedGoogle ScholarCrossref
21.
John  DA, Kawachi  I, Lathan  CS, Ayanian  JZ.  Disparities in perceived unmet need for supportive services among patients with lung cancer in the Cancer Care Outcomes Research and Surveillance Consortium.  Cancer. 2014;120(20):3178-3191.PubMedGoogle ScholarCrossref
22.
Hope-Stone  L, Brown  SL, Heimann  H, Damato  B, Salmon  P.  Two-year patient-reported outcomes following treatment of uveal melanoma.  Eye (Lond). 2016;30(12):1598-1605.PubMedGoogle ScholarCrossref
23.
Uchino  BN.  Social support and health: a review of physiological processes potentially underlying links to disease outcomes.  J Behav Med. 2006;29(4):377-387.PubMedGoogle ScholarCrossref
24.
Digman  J.  Personality structure: Emergence of the five-factor model.  Annu Rev Psychol. 1990;41(1):417-440.Google ScholarCrossref
25.
de Ridder  D, Geenen  R, Kuijer  R, van Middendorp  H.  Psychological adjustment to chronic disease.  Lancet. 2008;372(9634):246-255.PubMedGoogle ScholarCrossref
26.
Holladay  JT.  Visual acuity measurements.  J Cataract Refract Surg. 2004;30(2):287-290.PubMedGoogle ScholarCrossref
27.
Sherbourne  CD, Hays  RD, Ordway  L, DiMatteo  MR, Kravitz  RL.  Antecedents of adherence to medical recommendations: results from the Medical Outcomes Study.  J Behav Med. 1992;15(5):447-468.PubMedGoogle ScholarCrossref
28.
Rowland  JH, Desmond  KA, Meyerowitz  BE, Belin  TR, Wyatt  GE, Ganz  PA.  Role of breast reconstructive surgery in physical and emotional outcomes among breast cancer survivors.  J Natl Cancer Inst. 2000;92(17):1422-1429.PubMedGoogle ScholarCrossref
29.
Kemeny  NE, Niedzwiecki  D, Hollis  DR,  et al.  Hepatic arterial infusion versus systemic therapy for hepatic metastases from colorectal cancer: a randomized trial of efficacy, quality of life, and molecular markers (CALGB 9481).  J Clin Oncol. 2006;24(9):1395-1403.PubMedGoogle ScholarCrossref
30.
Costa  PT, McCrae  RR.  NEO Personality Inventory-Revised (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) Professional Manual. Odessa, FL: Psychological Assessment Resources; 1992.
31.
Dar-Nimrod  I, Chapman  BP, Franks  P,  et al.  Personality factors moderate the associations between apolipoprotein genotype and cognitive function as well as late onset Alzheimer disease.  Am J Geriatr Psychiatry. 2012;20(12):1026-1035.PubMedGoogle ScholarCrossref
32.
Asghari  A, Nicholas  MK.  Pain self-efficacy beliefs and pain behaviour: a prospective study.  Pain. 2001;94(1):85-100.PubMedGoogle ScholarCrossref
33.
Foot  G, Sanson-Fisher  R.  Measuring the unmet needs of people living with cancer.  Cancer Forum. 1995;19(2):131-135.Google Scholar
34.
Aranda  S, Schofield  P, Weih  L,  et al.  Mapping the quality of life and unmet needs of urban women with metastatic breast cancer.  Eur J Cancer Care (Engl). 2005;14(3):211-222.PubMedGoogle ScholarCrossref
35.
Chen  S-C, Liao  C-T, Lin  C-C, Chang  JT-C, Lai  Y-H.  Distress and care needs in newly diagnosed oral cavity cancer patients receiving surgery.  Oral Oncol. 2009;45(9):815-820.PubMedGoogle ScholarCrossref
36.
Hetz  SP, Tomasone  JR.  Supportive care needs of Canadian melanoma patients and survivors.  Can Oncol Nurs J. 2012;22(4):248-256.PubMedGoogle ScholarCrossref
37.
Smith  DP, Supramaniam  R, King  MT, Ward  J, Berry  M, Armstrong  BK.  Age, health, and education determine supportive care needs of men younger than 70 years with prostate cancer.  J Clin Oncol. 2007;25(18):2560-2566.PubMedGoogle ScholarCrossref
38.
Harrison  SE, Watson  EK, Ward  AM,  et al.  Primary health and supportive care needs of long-term cancer survivors: a questionnaire survey.  J Clin Oncol. 2011;29(15):2091-2098.PubMedGoogle ScholarCrossref
39.
Lam  WWT, Au  AHY, Wong  JHF,  et al.  Unmet supportive care needs: a cross-cultural comparison between Hong Kong Chinese and German Caucasian women with breast cancer.  Breast Cancer Res Treat. 2011;130(2):531-541.PubMedGoogle ScholarCrossref
40.
Hovén  E, Lannering  B, Gustafsson  G, Boman  KK.  The met and unmet health care needs of adult survivors of childhood central nervous system tumors: a double-informant, population-based study.  Cancer. 2011;117(18):4294-4303.PubMedGoogle ScholarCrossref
41.
Graham  JW.  Missing data analysis: making it work in the real world.  Annu Rev Psychol. 2009;60:549-576.PubMedGoogle ScholarCrossref
42.
Enders  C, Bandalos  D. The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Struct Equ Model A Multidiscip J. 2001;8(3):430–57.
43.
Minstrell  M, Winzenberg  T, Rankin  N, Hughes  C, Walker  J.  Supportive care of rural women with breast cancer in Tasmania, Australia: changing needs over time.  Psychooncology. 2008;17(1):58-65.PubMedGoogle ScholarCrossref
44.
Sutherland  G, Hill  D, Morand  M, Pruden  M, McLachlan  SA.  Assessing the unmet supportive care needs of newly diagnosed patients with cancer.  Eur J Cancer Care (Engl). 2009;18(6):577-584.PubMedGoogle ScholarCrossref
45.
McDowell  ME, Occhipinti  S, Ferguson  M, Dunn  J, Chambers  SK.  Predictors of change in unmet supportive care needs in cancer.  Psychooncology. 2010;19(5):508-516.PubMedGoogle ScholarCrossref
46.
Armes  J, Crowe  M, Colbourne  L,  et al.  Patients’ supportive care needs beyond the end of cancer treatment: a prospective, longitudinal survey.  J Clin Oncol. 2009;27(36):6172-6179.PubMedGoogle ScholarCrossref
47.
Collaborative Ocular Melanoma Study–Quality of Life Study Group.  Quality of life after iodine 125 brachytherapy vs enucleation for choroidal melanoma: 5-year results from the Collaborative Ocular Melanoma Study: COMS-QOLS report No. 3.  Arch Ophthalmol. 2006;124:226-238.PubMedGoogle ScholarCrossref
48.
Beesley  V, Eakin  E, Steginga  S, Aitken  J, Dunn  J, Battistutta  D.  Unmet needs of gynaecological cancer survivors: implications for developing community support services.  Psychooncology. 2008;17(4):392-400.PubMedGoogle ScholarCrossref
49.
Sherbourne  CD, Stewart  AL.  The MOS social support survey.  Soc Sci Med. 1991;32(6):705-714.PubMedGoogle ScholarCrossref
50.
Taylor  SE. Social support: a review. In: Friedman  HS, ed.  The Oxford Handbook of Health Psychology. New York, NY: Oxford University Press; 2011:189-214.
51.
Brissette  I, Cohen  S, Seeman  TE. Measuring social integration and social networks. In: Social Support Measurement and Intervention: A Guide for Health and Social Scientists. New York, NY: Oxford University Press; 2000:53-85.
52.
Carlson  LE, Waller  A, Mitchell  AJ.  Screening for distress and unmet needs in patients with cancer: review and recommendations.  J Clin Oncol. 2012;30(11):1160-1177.PubMedGoogle ScholarCrossref
53.
Butow  PN, Bell  ML, Smith  AB,  et al; Conquer Fear Authorship Group.  Conquer fear: protocol of a randomised controlled trial of a psychological intervention to reduce fear of cancer recurrence.  BMC Cancer. 2013;13(1):201.PubMedGoogle ScholarCrossref
54.
Fawzy  FI, Fawzy  NW.  A structured psychoeducational intervention for cancer patients.  Gen Hosp Psychiatry. 1994;16(3):149-192.PubMedGoogle ScholarCrossref
55.
Boesen  EH, Ross  L, Frederiksen  K,  et al.  Psychoeducational intervention for patients with cutaneous malignant melanoma: a replication study.  J Clin Oncol. 2005;23(6):1270-1277.PubMedGoogle ScholarCrossref
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