Evaluation of Older Age and Frailty as Factors Associated With Depression and Postoperative Decision Regret in Patients Undergoing Major Head and Neck Surgery | Depressive Disorders | JAMA Otolaryngology–Head & Neck Surgery | JAMA Network
[Skip to Navigation]
Table 1.  Study Population Demographics
Study Population Demographics
Table 2.  Survey Completion Rates
Survey Completion Rates
Table 3.  Variables Associated With Preoperative Moderate to Severe Depression Based on Univariate Analysis
Variables Associated With Preoperative Moderate to Severe Depression Based on Univariate Analysis
Table 4.  Variables Associated With Preoperative Moderate to Severe Depression Based on Multivariate Analysis
Variables Associated With Preoperative Moderate to Severe Depression Based on Multivariate Analysis
Table 5.  Variables Associated With Moderate to Severe Decision Regret on Univariate Analysis
Variables Associated With Moderate to Severe Decision Regret on Univariate Analysis
1.
Genther  DJ, Gourin  CG.  Effect of comorbidity on short-term outcomes and cost of care after head and neck cancer surgery in the elderly.  Head Neck. 2015;37(5):685-693. doi:10.1002/hed.23651PubMedGoogle ScholarCrossref
2.
Jégu  J, Binder-Foucard  F, Borel  C, Velten  M.  Trends over three decades of the risk of second primary cancer among patients with head and neck cancer.  Oral Oncol. 2013;49(1):9-14. doi:10.1016/j.oraloncology.2012.06.018PubMedGoogle ScholarCrossref
3.
Nieman  CL, Pitman  KT, Tufaro  AP, Eisele  DW, Frick  KD, Gourin  CG.  The effect of frailty on short-term outcomes after head and neck cancer surgery.  Laryngoscope. 2018;128(1):102-110. doi:10.1002/lary.26735PubMedGoogle ScholarCrossref
4.
Katz  MR, Kopek  N, Waldron  J, Devins  GM, Tomlinson  G.  Screening for depression in head and neck cancer.  Psychooncology. 2004;13(4):269-280. doi:10.1002/pon.734PubMedGoogle ScholarCrossref
5.
Fan  CY, Chao  HL, Lin  CS,  et al.  Risk of depressive disorder among patients with head and neck cancer: a nationwide population-based study.  Head Neck. 2018;40(2):312-323. doi:10.1002/hed.24961PubMedGoogle ScholarCrossref
6.
Kugaya  A, Akechi  T, Okuyama  T,  et al.  Prevalence, predictive factors, and screening for psychologic distress in patients with newly diagnosed head and neck cancer.  Cancer. 2000;88(12):2817-2823. doi:10.1002/1097-0142(20000615)88:12<2817::AID-CNCR22>3.0.CO;2-NPubMedGoogle ScholarCrossref
7.
Lazure  KE, Lydiatt  WM, Denman  D, Burke  WJ.  Association between depression and survival or disease recurrence in patients with head and neck cancer enrolled in a depression prevention trial.  Head Neck. 2009;31(7):888-892. doi:10.1002/hed.21046PubMedGoogle ScholarCrossref
8.
McCaffrey  JC, Weitzner  M, Kamboukas  D, Haselhuhn  G, Lamonde  L, Booth-Jones  M.  Alcoholism, depression, and abnormal cognition in head and neck cancer: a pilot study.  Otolaryngol Head Neck Surg. 2007;136(1):92-97. doi:10.1016/j.otohns.2006.06.1275PubMedGoogle ScholarCrossref
9.
Li  M, Kennedy  EB, Byrne  N,  et al.  Management of depression in patients with cancer: a clinical practice guideline.  J Oncol Pract. 2016;12(8):747-756. doi:10.1200/JOP.2016.011072PubMedGoogle ScholarCrossref
10.
Andersen  BL, DeRubeis  RJ, Berman  BS,  et al; American Society of Clinical Oncology.  Screening, assessment, and care of anxiety and depressive symptoms in adults with cancer: an American Society of Clinical Oncology guideline adaptation.  J Clin Oncol. 2014;32(15):1605-1619. doi:10.1200/JCO.2013.52.4611PubMedGoogle ScholarCrossref
11.
Andersen  BL, Rowland  JH, Somerfield  MR.  Screening, assessment, and care of anxiety and depressive symptoms in adults with cancer: an American Society of Clinical Oncology guideline adaptation.  J Oncol Pract. 2015;11(2):133-134. doi:10.1200/JOP.2014.002311PubMedGoogle ScholarCrossref
12.
Soysal  P, Veronese  N, Thompson  T,  et al.  Relationship between depression and frailty in older adults: a systematic review and meta-analysis.  Ageing Res Rev. 2017;36:78-87. doi:10.1016/j.arr.2017.03.005PubMedGoogle ScholarCrossref
13.
Korsten  LHA, Jansen  F, de Haan  BJF,  et al.  Factors associated with depression over time in head and neck cancer patients: a systematic review.  Psychooncology. 2019;28(6):1159-1183. doi:10.1002/pon.5058PubMedGoogle ScholarCrossref
14.
Brehaut  JC, O’Connor  AM, Wood  TJ,  et al.  Validation of a decision regret scale.  Med Decis Making. 2003;23(4):281-292. doi:10.1177/0272989X03256005PubMedGoogle ScholarCrossref
15.
Holmes-Rovner  M, Kroll  J, Schmitt  N,  et al.  Patient satisfaction with health care decisions: the satisfaction with decision scale.  Med Decis Making. 1996;16(1):58-64. doi:10.1177/0272989X9601600114PubMedGoogle ScholarCrossref
16.
Gill  SS, Frew  J, Fry  A,  et al.  Priorities for the head and neck cancer patient, their companion and members of the multidisciplinary team and decision regret.  Clin Oncol (R Coll Radiol). 2011;23(8):518-524. doi:10.1016/j.clon.2011.03.014PubMedGoogle ScholarCrossref
17.
Becerra Pérez  MM, Menear  M, Brehaut  JC, Légaré  F.  Extent and predictors of decision regret about health care decisions: a systematic review.  Med Decis Making. 2016;36(6):777-790. doi:10.1177/0272989X16636113PubMedGoogle ScholarCrossref
18.
Goepfert  RP, Fuller  CD, Gunn  GB,  et al.  Symptom burden as a driver of decisional regret in long-term oropharyngeal carcinoma survivors.  Head Neck. 2017;39(11):2151-2158. doi:10.1002/hed.24879PubMedGoogle ScholarCrossref
19.
Shuman  AG, Larkin  K, Thomas  D,  et al.  Patient reflections on decision making for laryngeal cancer treatment.  Otolaryngol Head Neck Surg. 2017;156(2):299-304. doi:10.1177/0194599816683377PubMedGoogle ScholarCrossref
20.
Groopman  J, Hartzband  P.  The power of regret.  N Engl J Med. 2017;377(16):1507-1509. doi:10.1056/NEJMp1709917PubMedGoogle ScholarCrossref
21.
Arora  VM, Johnson  M, Olson  J,  et al.  Using assessing care of vulnerable elders quality indicators to measure quality of hospital care for vulnerable elders.  J Am Geriatr Soc. 2007;55(11):1705-1711. doi:10.1111/j.1532-5415.2007.01444.xPubMedGoogle ScholarCrossref
22.
Min  L, Yoon  W, Mariano  J,  et al.  The Vulnerable Elders-13 survey predicts 5-year functional decline and mortality outcomes in older ambulatory care patients.  J Am Geriatr Soc. 2009;57(11):2070-2076. doi:10.1111/j.1532-5415.2009.02497.xPubMedGoogle ScholarCrossref
23.
McDowell  I, Praught  E.  On the measurement of happiness: an examination of the Bradburn scale in the Canada Health Survey.  Am J Epidemiol. 1982;116(6):949-958. doi:10.1093/oxfordjournals.aje.a113497PubMedGoogle ScholarCrossref
24.
Bradburn  N.  The Structure of Psychological Well-Being. Chicago, Illinois: Aldine Publishing Co; 1969.
25.
Chong  DK.  Measurement of instrumental activities of daily living in stroke.  Stroke. 1995;26(6):1119-1122. doi:10.1161/01.STR.26.6.1119PubMedGoogle ScholarCrossref
26.
Lawton  MP, Brody  EM.  Assessment of older people: self-maintaining and instrumental activities of daily living.  Gerontologist. 1969;9(3):179-186. doi:10.1093/geront/9.3_Part_1.179PubMedGoogle ScholarCrossref
27.
Aaronson  NK, Ahmedzai  S, Bergman  B,  et al.  The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology.  J Natl Cancer Inst. 1993;85(5):365-376. doi:10.1093/jnci/85.5.365PubMedGoogle ScholarCrossref
28.
Sheikh  J, Yesavage  J.  Geriatric Depression Scale (GDS): recent evidence and development of a shorter version.  Clin Gerontol. 1986;5:165-173. doi:10.1300/J018v05n01_09Google ScholarCrossref
29.
Mitchell  AJ, Bird  V, Rizzo  M, Meader  N.  Diagnostic validity and added value of the Geriatric Depression Scale for depression in primary care: a meta-analysis of GDS30 and GDS15.  J Affect Disord. 2010;125(1-3):10-17. doi:10.1016/j.jad.2009.08.019PubMedGoogle ScholarCrossref
30.
Fried  LP, Tangen  CM, Walston  J,  et al; Cardiovascular Health Study Collaborative Research Group.  Frailty in older adults: evidence for a phenotype.  J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-M156. doi:10.1093/gerona/56.3.M146PubMedGoogle ScholarCrossref
31.
Makary  MA, Segev  DL, Pronovost  PJ,  et al.  Frailty as a predictor of surgical outcomes in older patients.  J Am Coll Surg. 2010;210(6):901-908. doi:10.1016/j.jamcollsurg.2010.01.028PubMedGoogle ScholarCrossref
32.
O’Connor  AM.  Validation of a decisional conflict scale.  Med Decis Making. 1995;15(1):25-30. doi:10.1177/0272989X9501500105PubMedGoogle ScholarCrossref
33.
Cannady  SB, Hatten  KM, Bur  AM,  et al.  Use of free tissue transfer in head and neck cancer surgery and risk of overall and serious complication(s): an American College of Surgeons–National Surgical Quality Improvement Project analysis of free tissue transfer to the head and neck.  Head Neck. 2017;39(4):702-707. doi:10.1002/hed.24669PubMedGoogle ScholarCrossref
34.
Jain  U, Somerville  J, Saha  S,  et al.  Predictors of adverse events after neck dissection: an analysis of the 2006-2011 National Surgical Quality Improvement Program (NSQIP) database.  Ear Nose Throat J. 2017;96(2):E37-E45. doi:10.1177/014556131709600218PubMedGoogle ScholarCrossref
35.
Schwam  ZG, Sosa  JA, Roman  S, Judson  BL.  Complications and mortality following surgery for oral cavity cancer: analysis of 408 cases.  Laryngoscope. 2015;125(8):1869-1873. doi:10.1002/lary.25328PubMedGoogle ScholarCrossref
36.
Derks  W, De Leeuw  R, Winnubst  J, Hordijk  GJ.  Elderly patients with head and neck cancer: physical, social and psychological aspects after 1 year.  Acta Otolaryngol. 2004;124(4):509-514. doi:10.1080/00016480310000656PubMedGoogle ScholarCrossref
37.
Moubayed  SP, Sampalis  JS, Ayad  T,  et al.  Predicting depression and quality of life among long-term head and neck cancer survivors.  Otolaryngol Head Neck Surg. 2015;152(1):91-97. doi:10.1177/0194599814557772PubMedGoogle ScholarCrossref
38.
Lydiatt  WM, Bessette  D, Schmid  KK, Sayles  H, Burke  WJ.  Prevention of depression with escitalopram in patients undergoing treatment for head and neck cancer: randomized, double-blind, placebo-controlled clinical trial.  JAMA Otolaryngol Head Neck Surg. 2013;139(7):678-686. doi:10.1001/jamaoto.2013.3371PubMedGoogle Scholar
39.
Martinez  KA, Li  Y, Resnicow  K, Graff  JJ, Hamilton  AS, Hawley  ST.  Decision regret following treatment for localized breast cancer: is regret stable over time?  Med Decis Making. 2015;35(4):446-457. doi:10.1177/0272989X14564432PubMedGoogle ScholarCrossref
40.
Puts  MTE, Hsu  T, Mariano  C,  et al.  Clinical and cost-effectiveness of a comprehensive geriatric assessment and management for Canadian elders with cancer—the 5C study: a study protocol for a randomised controlled phase III trial.  BMJ Open. 2019;9(5):e024485. doi:10.1136/bmjopen-2018-024485PubMedGoogle ScholarCrossref
41.
Puts  MTE, Strohschein  FJ, Del Giudice  ME,  et al.  Role of the geriatrician, primary care practitioner, nurses, and collaboration with oncologists during cancer treatment delivery for older adults: a narrative review of the literature.  J Geriatr Oncol. 2018;9(4):398-404. doi:10.1016/j.jgo.2018.04.008PubMedGoogle ScholarCrossref
42.
Bagayogo  FF, Lepage  A, Denis  JL, Lamothe  L, Lapointe  L, Vedel  I.  Factors influencing cancer specialists’ decision to collaborate with geriatricians in treating older cancer patients.  Age Ageing. 2016;45(5):723-726. doi:10.1093/ageing/afw101PubMedGoogle ScholarCrossref
43.
Shuman  AG, Korc-Grodzicki  B, Shklar  V, Palmer  F, Shah  JP, Patel  SG.  A new care paradigm in geriatric head and neck surgical oncology.  J Surg Oncol. 2013;108(3):187-191. doi:10.1002/jso.23370PubMedGoogle ScholarCrossref
44.
Birrer  RB, Vemuri  SP.  Depression in later life: a diagnostic and therapeutic challenge.  Am Fam Physician. 2004;69(10):2375-2382.PubMedGoogle Scholar
45.
de Graeff  A, de Leeuw  JR, Ros  WJ, Hordijk  GJ, Blijham  GH, Winnubst  JA.  Long-term quality of life of patients with head and neck cancer.  Laryngoscope. 2000;110(1):98-106. doi:10.1097/00005537-200001000-00018PubMedGoogle ScholarCrossref
46.
Bui  AT, Yong Ji  KS, Pham  CT, Le  KM, Tong  TX, Lee  WT.  Longitudinal evaluation of quality of life in laryngeal cancer patients treated with surgery.  Int J Surg. 2018;58:65-70. doi:10.1016/j.ijsu.2018.09.011PubMedGoogle ScholarCrossref
47.
Diefenbach  MA, Mohamed  NE.  Regret of treatment decision and its association with disease-specific quality of life following prostate cancer treatment.  Cancer Invest. 2007;25(6):449-457. doi:10.1080/07357900701359460PubMedGoogle ScholarCrossref
48.
Hurwitz  LM, Cullen  J, Kim  DJ,  et al.  Longitudinal regret after treatment for low- and intermediate-risk prostate cancer.  Cancer. 2017;123(21):4252-4258. doi:10.1002/cncr.30841PubMedGoogle ScholarCrossref
49.
Lavery  HJ, Levinson  AW, Hobbs  AR,  et al.  Baseline functional status may predict decisional regret following robotic prostatectomy.  J Urol. 2012;188(6):2213-2218. doi:10.1016/j.juro.2012.08.016PubMedGoogle ScholarCrossref
Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words
    Original Investigation
    October 17, 2019

    Evaluation of Older Age and Frailty as Factors Associated With Depression and Postoperative Decision Regret in Patients Undergoing Major Head and Neck Surgery

    Author Affiliations
    • 1Department of Otolaryngology–Head and Neck Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada
    • 2Department of Surgical Oncology, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada
    • 3Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
    • 4Department of Biostatistics, Princess Margaret Cancer Centre/University Health Network, Toronto, Ontario, Canada
    • 5Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
    • 6Department of Medicine, University of Toronto, Toronto, Ontario, Canada
    • 7Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada
    • 8Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
    JAMA Otolaryngol Head Neck Surg. 2019;145(12):1170-1178. doi:10.1001/jamaoto.2019.3020
    Key Points

    Question  Do elderly or frail patients with head and neck cancer have worse depression and higher rates of decision regret after surgery?

    Findings  In this cohort study, the prevalence of preoperative moderate to severe depression was 9.6% and the prevalence of moderate to severe decision regret was 26.7%. Elderly patients (≥65 years) did not have increased depression or decision regret; however, higher frailty scores are associated with depression and worse depression is associated with decision regret.

    Meaning  Identifying at-risk populations and understanding factors associated with depression and decision regret allows for targeted preoperative and postoperative treatment and counseling.

    Abstract

    Importance  Clinicians should understand the prevalence of depression and decision regret in patients with head and neck cancer and whether these factors differ with age or frailty.

    Objectives  To assess whether age and frailty are associated with preoperative and/or worsening postoperative depression and postoperative decision regret in patients undergoing major head and neck surgery and to identify additional factors associated with depression and decision regret.

    Design, Setting, and Participants  This prospective cohort study was conducted at a single institution, with patients aged 50 years or older undergoing major head and neck surgery recruited from December 1, 2011, to April 30, 2014. Statistical analysis was performed from July 1, 2018, to June 30, 2019.

    Main Outcomes and Measures  Frailty, functional, and geriatric depression assessments were completed before surgery and 3, 6, and 12 months after surgery. Decision regret assessment was completed 6 months after surgery. The prevalence of depression and decision regret was determined by age group. Change in depression over time was compared between age groups using a linear-effects model. Variables potentially associated with moderate to severe depression and decision regret were analyzed using a logistic regression model.

    Results  The study included 274 patients (68 women and 206 men; mean [SD] age, 67.8 [9.5] years). Of these, 105 (38.3%) were 50 to 64 years of age and 169 (61.7%) were 65 years or older. The rate of preoperative moderate to severe depression was 9.6% (21 of 219), with no difference between younger and older adult cohorts. For both age groups, depression scores increased in the postoperative period from baseline to 6 months. At 12 months, there was a difference in depression scores between the younger and older adult cohort (4.8 [4.6] vs 3.1 [3.6]). A higher preoperative Fried Frailty Index score (odds ratio, 2.58 [95% CI, 1.63-4.06]) was associated with preoperative moderate to severe depression. For all patients, the mean Decision Regret Scale score was 18.2 (range, 0-95), and 26.7% of patients (48 of 180) had moderate to severe regret. There was no difference in Decision Regret Scale scores between younger and older patients. Preoperative depression but not frailty is associated with postoperative moderate to severe decision regret (odds ratio, 1.17 [95% CI, 1.06-1.28]).

    Conclusions and Relevance  In this cohort study, there was no difference based on age in the prevalence of moderate to severe depression or decision regret. A higher preoperative frailty score was associated with depression but not decision regret. Preoperative depression was the only factor associated with moderate to severe decision regret on multivariate analysis. Understanding the prevalence of and factors associated with moderate to severe depression and decision regret may aid in identifying patients who would benefit from more extensive preoperative counseling and preoperative and postoperative multispecialty assessment and treatment.

    Introduction

    Head and neck cancer (HNC) occurs frequently in older patients; with a rapidly aging population, there will be an increased need for HNC surgery.1,2 Older patients with HNC have unique vulnerabilities, and treatment may have a differential effect on older compared with younger patients. There is a growing body of literature demonstrating frailty’s association with negative postoperative outcomes, such as complications, increased hospital length of stay, and increased levels of care, after HNC surgery.3 However, there is a lack of understanding of the role that age and frailty play in preoperative and postoperative depression and regret with treatment decisions after HNC surgery.

    Approximately 20% to 30% of all patients with cancer will experience depression at some point during their disease process.4 Patients with HNC have one of the highest rates of depression, with a prevalence reported up to 57%, although the rates vary between studies and the time periods evaluated.5-8 Although there has been a recommendation toward screening all patients with cancer for depression,9-11 given the variable rates and limitations to health care resources, a more selective approach to screening patients at higher risk for depression may be more feasible. Thus, identifying factors that put patients at higher risk of depression prior to and after treatment is important. A recent meta-analysis on frailty and depression in the elderly nonsurgical population found the prevalence of depression in frail patients to be 39% and the prevalence of frailty in depressed patients to be 40%.12 Each condition increased the odds of the other. A recent systematic review examined 69 factors possibly associated with depression in patients with HNC and found that the only factor associated with depression was prior symptoms of depression.13 Frailty was not examined in this comprehensive review. The association between frailty and depression has yet to be clearly examined in patients with HNC.

    Decision regret in health care has been defined as “remorse or distress over a treatment decision,”14(p282)15 with the concept of regret being “the negative, cognitively-based emotion experienced when realizing or imagining that the present situation would have been better had we acted differently.”16(p519) A systematic review of studies using the Decision Regret Scale (DRS) demonstrated no association of age with decision regret; however, posttreatment complications, adverse outcomes, and increased hospital length of stay were associated with higher levels of regret.17 Within the HNC literature, 2 studies have assessed decision regret.18,19 In these studies, decision regret is associated with posttreatment symptom burden in patients with oropharyngeal cancer and with voice-related quality of life (QoL) in patients with laryngeal cancer. To our knowledge, the association of age and frailty with decision regret has not been extensively studied in surgical oncology, including HNC surgery. Regret is a complex emotion with potentially significant consequences and is intimately related to the decision-making process.20 Often, there are several treatment options available to patients with HNC. It is important to identify patients at risk for decision regret and depression to assist them with understanding treatment options and sequelae and help them make a treatment choice that is correct for them.

    The primary objective of this study was to assess the association between age and frailty and preoperative and postoperative depression as well as postoperative decision regret in patients with HNC treated with surgery. The secondary objective was to determine additional factors associated with depression and decision regret.

    Methods

    A prospective cohort study was performed of patients aged 50 years or older undergoing major head and neck surgery between December 1, 2011, and April 30, 2014. Patients were eligible for inclusion if they planned to undergo major surgery for management of either primary or recurrent HNC or for a late effect of head and neck radiotherapy, which included total laryngectomy with bilateral neck dissections, surgical resection requiring microvascular free flap or regional myocutaneous flap reconstruction, parotidectomy or thyroidectomy with lateral neck dissection, or resection of cutaneous malignant neoplasms with neck dissection and/or microvascular free flap reconstruction. Tumor site was classified as either mucosal (oral cavity, oropharynx, larynx, and hypopharynx) or nonmucosal (cutaneous, thyroid, and salivary gland). Eligible patients were recruited from head and neck surgery clinics after a decision to operate was made. Written informed consent was obtained from all patients who participated in the study. Research ethics board approval was obtained from University Health Network and Princess Margaret Cancer Centre.

    At baseline, patients completed the following patient reported outcomes (PROs): Vulnerable Elders Survey (VES-13), Bradburn Scale of Psychological Well-Being, Lawton-Brody Instrumental Activities of Daily Living (IADL) Questionnaire, European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), and the Geriatric Depression Scale (GDS). The VES-13 is a 13-item function-based tool designed to screen older patients at risk for health deterioration, with a higher overall score indicating greater vulnerability and decreased function.21,22 The Bradburn Scale of Psychological Well-Being assesses happiness, where a higher score indicates greater psychological well-being.23,24 The Lawton-Brody IADL Questionnaire is an 8-item tool designed to evaluate functioning,25,26 where a higher summary score represents greater levels of independence. The EORTC QLQ-C30 is a 30-item validated questionnaire with 5 functional scales, 3 symptom scales, global health status, and perceived financial effect that assesses QoL in patients with cancer, from which a summary score can be calculated, with a higher score indicating better QoL.27 The GDS is a 15-question yes or no scale that assesses depression in older adults, with a higher score indicating greater levels of depression (0-4 indicates no depression; 5-9, mild depression; and 10-15, moderate to severe depression).28 The short-form GDS was used, which has been validated in patients age 55 years or older.28,29 Worsening depression is defined as the GDS score increasing from 1 depression category classification to the next (ie, from mild depression to moderate or severe depression at a later time point).

    The research assistant collected sociodemographic data and completed the Adult Comorbidity Evaluation–27 instrument (used to determine a comorbidity score of none, mild, moderate, or severe) and the Fried Frailty Index, which measures frailty in 5 domains (shrinking or weight loss, decreased grip strength or weakness, exhaustion, low physical activity, and slow walking speed).30 For each of the 5 items, patients are scored either 0 (criterion not met as being frail) or 1 (criterion met as being frail). Methods of measurement for each item were the same as those described by Makary et al.31 Perioperative data collected included postoperative surgical complications and disease status throughout follow-up.

    The same PROs were completed at the 3-, 6-, and 12-month postoperative visits, along with completion of the DRS at the 6-month visit. The DRS is a 5-item survey that has been validated in oncology patients.14,32 Decision Regret Scale responses are scaled from 1 (strongly agree) to 5 (strongly disagree) and standardized by multiplying by 25. Questions 2 and 4 are reverse coded. The scores are summed and higher scores indicate greater decision regret (0 indicates no regret; 1-25, mild regret; and >25, moderate to strong regret).14

    Statistical analysis was performed from July 1, 2018, to June 30, 2019, using SAS, version 9.4 (SAS Institute Inc) and R, version 3.1.2 (R Foundation for Statistical Computing). Patients were categorized into a younger (50-64 years) or older (≥65 years) age group. The primary outcomes were GDS and DRS scores. Change in depression over time between age groups was examined using a linear-effects model. Repeated measure analysis was applied on a continuous GDS score, repeated categorical time points (before surgery and 3, 6, and 12 months after surgery), and categorical age groups. Unstructured covariance structure was used based on the smallest Akaike information criterion. Variables potentially associated with moderate to severe depression and moderate to severe decision regret were analyzed using logistic regression models. Age was examined as both a categorical and continuous variable. Potential factors associated with each outcome (P < .10) were chosen for the model selection. The multivariate (MVA) models were created from these models. Odds ratios (ORs) are provided with 95% CIs. Missing data were addressed via sensitivity analysis using imputation. First, mean scores of respondents who provided data at each time point were used to impute scores for missing data. Second, the upper quintile of provided data for each time point was imputed (high score indicates worse result) to determine if results are sensitive to the assumption of missing at random. All P values were derived from 2-sided tests, and results were deemed statistically significant at P < .05.

    Results

    A total of 274 patients (mean [SD] age, 67.8 [9.5] years) were enrolled, of which 105 were aged 50 to 64 years (23 [8.4%] were aged 50-54 years) and 169 were age 65 years or older. Demographic and clinical variables are summarized in Table 1. Most patients were male (206 [75.2%]), married or in common-law marriage (167 of 234 [71.4%]), and had postsecondary education (122 of 214 [57.0%]). The primary tumor site was categorized as mucosal (158 of 271 [58.3%]) vs nonmucosal (113 of 271 [41.7%]). Microvascular reconstruction was performed in 212 patients (77.4%). Surgical complications occurred in 114 study participants (41.6%). Twenty-five patients were alive with disease at 6 months and 16 patients were alive with disease at 12 months.

    There was 100% completion (n = 274) of the baseline Fried Frailty Index, and 251 patients were enrolled in the longitudinal study. Twenty-three patients completed only the baseline frailty assessment because they either opted out of the longitudinal portion of the study or were recruited in the last 6 months of the study period and were not able to complete the follow-up assessments. Table 2 details the number of patients who completed the various PROs at each time point. At baseline, 218 patients completed all PROs, with 177 completed at 3 months, 161 completed at 6 months, and 115 completed at 12 months). Reasons for incomplete PROs included patient deaths (n = 36), withdrawal from the study (n = 9), general loss to follow-up, incomplete survey completion within patient study packets, and late enrollment with no long-term follow up before the study concluded (n = 12). Sensitivity analysis revealed that missing data did not bias the findings and conclusions of our study (eTable in the Supplement).

    Depression

    Preoperatively at baseline, 161 of 219 patients (73.5%) were not depressed, 37 of 219 patients (16.9%) had mild depression, and 21 of 219 patients (9.6%) had moderate to severe depression, with no difference in the prevalence of depression between age groups. The mean (SD) preoperative GDS score was 3.3 (3.4); there was no difference between the younger and older cohort in mean GDS score. For both age groups, depression scores increased in the postoperative period from baseline to 6 months. At 12 months, there was a difference in depression scores between the younger and older adult cohort (4.8 [4.6] vs 3.1 [3.6]). However, when examining the trajectory of change in depression scores over time, there was no difference between the age groups (mean difference, 0.99 [95% CI, −0.04 to 2.01]). Overall, at 12 months, 20.2% of patients (33 of 163) had worsening depression and 73.6% (120 of 163) remained stable.

    Univariate factors associated with moderate to severe depression at baseline are presented in Table 3. Factors associated with preoperative depression included age, mucosal tumor site, higher Fried Frailty Index score, and lower Bradburn Scale of Psychological Well-Being and EORTC QLQ-C30 scores. In MVA models, higher frailty score but not age was independently associated with moderate to severe depression at baseline (OR, 2.58 [95% CI, 1.63-4.06]). The effect was more pronounced in the older than the younger cohort (OR, 4.06 [95% CI, 1.88-8.74] vs 2.03 [95% CI, 1.05-3.92]). Additional factors associated with baseline depression in MVA models are presented in Table 4. In MVA models, preoperative scores on the VES-13 and Lawton-Brody IADL Questionnaire were not associated with preoperative depression, while a lower preoperative EORTC QLQ-C30 summary score (OR, 0.89 [95% CI, 0.86-0.92]) and Bradburn Scale of Psychological Well-Being score (OR, 0.44 [95% CI, 0.34-0.57]) were associated with preoperative depression. In addition, lower baseline Bradburn Scale of Psychological Well-Being and EORTC QLQ-C30 summary scores were associated with worsening depression at the 6- and 12-month postoperative time points. Baseline Fried Frailty Index score, VES-13, and Lawton-Brody IADL Questionnaire scores were not associated with worsening depression in the postoperative time period. Examining the prevalence of preoperative depression stratified by frailty score revealed that frail patients have a 50.0% rate of moderate to severe depression (7 of 14 patients) compared with 2.9% (3 of 105 patients) in the cohort of patients who are not frail. As seen in the study by Soysal et al,12 being classified as frail (score, 3-5) increases the odds of having depression to a clinically significant level (OR, 13.64 [95% CI, 4.19-44.39]).

    Decision Regret

    The mean DRS score was 18.2 (range, 0-95), indicating that patients who underwent major HNC surgery had mild decision regret. Overall, 66 of 180 patients (36.7%) had no regret, 66 of 180 patients (36.7%) had mild regret, and 48 of 180 (26.7%) had moderate to severe regret. There was no difference in the mean DRS score or the percentage of patients with moderate to severe regret between the young and older adult cohorts (19.7 vs 16.9). Univariable baseline factors associated with moderate to severe decision regret 6 months after surgery (Table 5) included a higher Fried Frailty Index score (OR, 1.38 [95% CI, 1.01-1.90]), higher depression scores (OR, 1.17 [95% CI, 1.06-1.28]), lower Lawton-Brody IADL Questionnaire scores (ie, increased dependence) (OR, 0.85 [95% CI, 0.75-0.97]), and lower score on the Bradburn Scale of Psychological Well-Being (ie, less happiness) (OR, 0.78 [95% CI, 0.68-0.91]). Both the preoperative and 6-month postoperative EORTC QLQ-C30 summary score was associated with moderate to severe decision regret at 6 months. In MVA models, only a higher preoperative depression score was associated with moderate to severe decision regret (OR, 1.17 [95% CI, 1.06-1.28]).

    Discussion

    To our knowledge, this prospective cohort study is the first to examine the association of age and frailty with depression and decision regret in patients with HNC. Our study group accurately represents the complexity of the HNC surgical population with a broad range of primary tumor sites and most patients requiring microvascular reconstruction (77.4%). The rate of surgical complications (114 [41.6%]) is within rates of postoperative complications reported in the literature.33-35

    The reported rates of depression in the literature in patients with HNC vary significantly. Our study revealed a preoperative rate of moderate to severe depression of 9.6%, which is at the lower end of previously reported rates, with no difference between age groups. The association of age with the prevalence of depression in HNC has been variably reported. Derks et al36 demonstrated an increase in depression during the first year after treatment for HNC but no difference between younger (45-60 years) and elderly (≥70 years) patients. In contrast, Fan et al5 demonstrated that the adjusted hazard ratio for depressive disorder decreased with increasing age. In our study in the preoperative period, there was no difference between the younger and older cohorts in rates of depression. Although we did observe a difference in rates of depression between age groups at 12 months after surgery, there was no difference in the trajectory of change in depression scores between age groups. It is possible that one may see a divergence in depression between age groups if patients are followed up for longer than 12 months.

    Although age was not associated with moderate to severe depression in MVA models, frailty was a clinically significant factor associated with depression. A recent systematic review and meta-analysis examining the association between depression and frailty in older adults found a reciprocal interaction with frailty increasing the odds of depression and depression increasing the odds of frailty when controlling for confounding factors.12 In our own study population, examining the prevalence of moderate to severe depression in frail patients revealed a high rate of depression (50%) compared with intermediate frail and not frail patients. Depression can be intervened on and usually ameliorated37; therefore, there are guidelines for the management of depression in patients with cancer, with recommendations for screening all patients for depression.9-11 Currently, there are no guidelines for depression management specific to HNC. A study by Lydiatt et al38 demonstrated that patients with HNC treated with the antidepressant escitalopram at the initiation of treatment had more than 50% reduction in their risk of developing depression as well as improved QoL assessed using the University of Washington Quality of Life Scale. The literature has shown that depression and suicide are major problems in patients with HNC. Given the volume of patients seen within head and neck clinics and limitations in resources, there is a potential benefit to focused screening of at-risk populations compared with mass screening. This strategy may allow for improved identification and management of patients within resource constraints. Based on the results of our study, frail patients could be identified preoperatively for targeted depression screening and treatment with either pharmacologic therapy or psychotherapy. This area should be studied formally.

    Changes in depression over time were examined, with depression worsening in the postoperative period in 20.2% of our study population. Lower preoperative Bradburn Scale of Psychological Well-Being and EORTC QLQ-C30 summary scores are preoperative factors associated with worsening postoperative depression. The Bradburn Scale of Psychological Well-Being assesses psychological well-being or happiness, and clinically it makes sense that decreased happiness is associated with baseline and worsening depression. The EORTC QLQ-C30 is a comprehensive measure of QoL in patients with cancer, and as seen in other studies, decreased QoL is associated with depression.37 This fact emphasizes the need to identify and treat depression as well as the risk factors for depression in patients with HNC.

    Decision regret is an important survivorship issue; however, to our knowledge, it has not been extensively assessed in patients with HNC. Recently, Goepfert et al18 reported on decision regret in survivors of oropharyngeal squamous cell carcinoma. Their cohort of 972 patients had a 15.5% rate of moderate to severe regret, which is lower than the rate we observed. Overall symptom score was associated with decision regret in MVA models as was treatment group with primary chemoradiotherapy and surgery plus postoperative radiotherapy having the highest decision regret. A systematic review of studies using the DRS (n = 59) demonstrated an overall DRS score of 16.5,17 which is comparable to the score of 18.2 in our study. The rate of moderate to severe decision regret was 26.7% in our study population. This rate of decision regret demonstrates that, while most patients with HNC are satisfied with their decision 6 months after surgery independent of age, there is still almost a 30% rate of moderate to severe decision regret that deserves to be identified and addressed.

    There was no difference in the percentage of patients reporting moderate to severe regret between the younger and older adult cohorts. Similarly, a study by Derks et al36 found that 92% of elderly patients with HNC assessed 1 year after surgical and nonsurgical treatments would make the same treatment decision again. On MVA modeling, only higher depression score was associated with decision regret and thus demonstrates another reason for managing depression. In contrast to decision regret studies in breast cancer, in which disease recurrence was associated with decision regret, in our study, disease recurrence was not associated with decision regret.39 Finally, frailty was not associated with decision regret in MVA models.

    There are emerging studies demonstrating the clinical usefulness of oncology care models incorporating geriatricians into treatment decisions and management of elderly oncology patients.40 Pilot studies have demonstrated that multidisciplinary management of older adult oncology patients decreases toxic effects of cancer treatment and improves supportive care and QoL.41 Geriatric assessment assists with estimating postsurgical complications and hospital length of stay and can facilitate discharge planning and initiation of rehabilitation.42,43 Depression in geriatric patients has an extended course of treatment compared with younger patients, as well as different considerations for pharmacotherapy.44 Identifying frail patients as a unique subset of patients with HNC with higher rates of depression reinforces the benefit of multidisciplinary care of these patients.

    Limitations

    One of the limitations of this study is the lack of long-term follow-up assessment for either the depression analysis (past 1 year) or decision regret (past 6 months). We selected 6 months for decision regret analysis as we wanted to ensure that we captured the patients at risk of dying within the first year. In the literature, the 3- to 6-month postoperative time points have been associated with the greatest decrease in QoL after HNC treatment.45,46 Further areas of study should include longitudinal decision regret assessment of patients with HNC as well as comparisons between surgical, radiotherapy, and chemoradiotherapy treatments. A 12-month assessment of decision regret would have been valuable, as decision regret has been shown in other cancers to change over time. For example, studies in prostate cancer have shown decision regret to increase over time.47-49 It is possible that a similar trend exists in patients with HNC, or perhaps decision regret decreases with time as QoL improves over 1 year and beyond in the postoperative period. Prior treatment or recurrence or complication of prior treatment was not assessed as a driver of depression and decision regret. Additional limitations include the small number of patients included in some of the subgroup analyses and the selection of the instruments used to assess PROs. For example, the GDS was developed to specifically assess unique characteristics of depression in the elderly. Although validated for patients aged 55 years or older, use of this instrument may have prevented recognizing depression in the younger cohort. However, the number of patients aged 50 to 54 years was low in our study (23 [8.4%]). Finally, there are missing data owing to patient withdrawal from the study, deaths, noncompliance, and patients who were recruited late and had only a 3-month follow-up before the study closed (Table 2). We performed sensitivity analyses to ensure that the missing data were not a source of bias in the study. Although sensitivity analyses confirmed that missing data did not bias the study results (eTable in the Supplement), the rate of survey completion remains a major limitation of this study.

    Conclusions

    Frail patients are a unique subset of patients with HNC with higher rates of depression. Patients with higher rates of depression are at risk for decision regret after surgery. Understanding the prevalence of and factors associated with depression and decision regret will aid in counseling patients and identifying frail patients who would benefit from more extensive preoperative counseling and postoperative multidisciplinary specialty assessment and treatment.

    Back to top
    Article Information

    Accepted for Publication: August 15, 2019.

    Corresponding Author: David P. Goldstein, MD, MSc, Department of Otolaryngology–Head and Neck Surgery, Princess Margaret Cancer Centre, University Health Network, University of Toronto, 610 University Ave, Ste 3-950, Toronto, ON M5G 2M9, Canada (david.goldstein@uhn.ca).

    Published Online: October 17, 2019. doi:10.1001/jamaoto.2019.3020

    Author Contributions: Drs Thomas and Goldstein had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Thomas, Sklar, Xu, Gilbert, Alibhai, Goldstein.

    Acquisition, analysis, or interpretation of data: Thomas, Su, Xu, de Almeida, Gullane, Brown, Irish, Alibhai, Goldstein.

    Drafting of the manuscript: Thomas, Sklar, Irish, Alibhai.

    Critical revision of the manuscript for important intellectual content: Sklar, Su, Xu, de Almeida, Gullane, Gilbert, Brown, Alibhai, Goldstein.

    Statistical analysis: Su, Xu, Alibhai.

    Obtained funding: Sklar, Goldstein.

    Administrative, technical, or material support: Gilbert, Irish, Alibhai, Goldstein.

    Supervision: Xu, de Almeida, Brown, Alibhai.

    Conflict of Interest Disclosures: Dr Sklar reported receiving a PSI Foundation Resident Research Grant and grants from Ontario Academic Health Sciences Centres Alternate Funding Plan Innovation Fund and University of Toronto Dean’s Fund during the conduct of the study. No other disclosures were reported.

    Funding/Support: Funding included PSI Foundation Resident Research Grant (Dr Sklar), Ontario Academic Health Sciences Centres Alternate Funding Plan Innovation Fund (Ontario Ministry of Health), and the University of Toronto Dean’s Fund.

    Role of the Funder/Sponsor: The funding sources 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.

    References
    1.
    Genther  DJ, Gourin  CG.  Effect of comorbidity on short-term outcomes and cost of care after head and neck cancer surgery in the elderly.  Head Neck. 2015;37(5):685-693. doi:10.1002/hed.23651PubMedGoogle ScholarCrossref
    2.
    Jégu  J, Binder-Foucard  F, Borel  C, Velten  M.  Trends over three decades of the risk of second primary cancer among patients with head and neck cancer.  Oral Oncol. 2013;49(1):9-14. doi:10.1016/j.oraloncology.2012.06.018PubMedGoogle ScholarCrossref
    3.
    Nieman  CL, Pitman  KT, Tufaro  AP, Eisele  DW, Frick  KD, Gourin  CG.  The effect of frailty on short-term outcomes after head and neck cancer surgery.  Laryngoscope. 2018;128(1):102-110. doi:10.1002/lary.26735PubMedGoogle ScholarCrossref
    4.
    Katz  MR, Kopek  N, Waldron  J, Devins  GM, Tomlinson  G.  Screening for depression in head and neck cancer.  Psychooncology. 2004;13(4):269-280. doi:10.1002/pon.734PubMedGoogle ScholarCrossref
    5.
    Fan  CY, Chao  HL, Lin  CS,  et al.  Risk of depressive disorder among patients with head and neck cancer: a nationwide population-based study.  Head Neck. 2018;40(2):312-323. doi:10.1002/hed.24961PubMedGoogle ScholarCrossref
    6.
    Kugaya  A, Akechi  T, Okuyama  T,  et al.  Prevalence, predictive factors, and screening for psychologic distress in patients with newly diagnosed head and neck cancer.  Cancer. 2000;88(12):2817-2823. doi:10.1002/1097-0142(20000615)88:12<2817::AID-CNCR22>3.0.CO;2-NPubMedGoogle ScholarCrossref
    7.
    Lazure  KE, Lydiatt  WM, Denman  D, Burke  WJ.  Association between depression and survival or disease recurrence in patients with head and neck cancer enrolled in a depression prevention trial.  Head Neck. 2009;31(7):888-892. doi:10.1002/hed.21046PubMedGoogle ScholarCrossref
    8.
    McCaffrey  JC, Weitzner  M, Kamboukas  D, Haselhuhn  G, Lamonde  L, Booth-Jones  M.  Alcoholism, depression, and abnormal cognition in head and neck cancer: a pilot study.  Otolaryngol Head Neck Surg. 2007;136(1):92-97. doi:10.1016/j.otohns.2006.06.1275PubMedGoogle ScholarCrossref
    9.
    Li  M, Kennedy  EB, Byrne  N,  et al.  Management of depression in patients with cancer: a clinical practice guideline.  J Oncol Pract. 2016;12(8):747-756. doi:10.1200/JOP.2016.011072PubMedGoogle ScholarCrossref
    10.
    Andersen  BL, DeRubeis  RJ, Berman  BS,  et al; American Society of Clinical Oncology.  Screening, assessment, and care of anxiety and depressive symptoms in adults with cancer: an American Society of Clinical Oncology guideline adaptation.  J Clin Oncol. 2014;32(15):1605-1619. doi:10.1200/JCO.2013.52.4611PubMedGoogle ScholarCrossref
    11.
    Andersen  BL, Rowland  JH, Somerfield  MR.  Screening, assessment, and care of anxiety and depressive symptoms in adults with cancer: an American Society of Clinical Oncology guideline adaptation.  J Oncol Pract. 2015;11(2):133-134. doi:10.1200/JOP.2014.002311PubMedGoogle ScholarCrossref
    12.
    Soysal  P, Veronese  N, Thompson  T,  et al.  Relationship between depression and frailty in older adults: a systematic review and meta-analysis.  Ageing Res Rev. 2017;36:78-87. doi:10.1016/j.arr.2017.03.005PubMedGoogle ScholarCrossref
    13.
    Korsten  LHA, Jansen  F, de Haan  BJF,  et al.  Factors associated with depression over time in head and neck cancer patients: a systematic review.  Psychooncology. 2019;28(6):1159-1183. doi:10.1002/pon.5058PubMedGoogle ScholarCrossref
    14.
    Brehaut  JC, O’Connor  AM, Wood  TJ,  et al.  Validation of a decision regret scale.  Med Decis Making. 2003;23(4):281-292. doi:10.1177/0272989X03256005PubMedGoogle ScholarCrossref
    15.
    Holmes-Rovner  M, Kroll  J, Schmitt  N,  et al.  Patient satisfaction with health care decisions: the satisfaction with decision scale.  Med Decis Making. 1996;16(1):58-64. doi:10.1177/0272989X9601600114PubMedGoogle ScholarCrossref
    16.
    Gill  SS, Frew  J, Fry  A,  et al.  Priorities for the head and neck cancer patient, their companion and members of the multidisciplinary team and decision regret.  Clin Oncol (R Coll Radiol). 2011;23(8):518-524. doi:10.1016/j.clon.2011.03.014PubMedGoogle ScholarCrossref
    17.
    Becerra Pérez  MM, Menear  M, Brehaut  JC, Légaré  F.  Extent and predictors of decision regret about health care decisions: a systematic review.  Med Decis Making. 2016;36(6):777-790. doi:10.1177/0272989X16636113PubMedGoogle ScholarCrossref
    18.
    Goepfert  RP, Fuller  CD, Gunn  GB,  et al.  Symptom burden as a driver of decisional regret in long-term oropharyngeal carcinoma survivors.  Head Neck. 2017;39(11):2151-2158. doi:10.1002/hed.24879PubMedGoogle ScholarCrossref
    19.
    Shuman  AG, Larkin  K, Thomas  D,  et al.  Patient reflections on decision making for laryngeal cancer treatment.  Otolaryngol Head Neck Surg. 2017;156(2):299-304. doi:10.1177/0194599816683377PubMedGoogle ScholarCrossref
    20.
    Groopman  J, Hartzband  P.  The power of regret.  N Engl J Med. 2017;377(16):1507-1509. doi:10.1056/NEJMp1709917PubMedGoogle ScholarCrossref
    21.
    Arora  VM, Johnson  M, Olson  J,  et al.  Using assessing care of vulnerable elders quality indicators to measure quality of hospital care for vulnerable elders.  J Am Geriatr Soc. 2007;55(11):1705-1711. doi:10.1111/j.1532-5415.2007.01444.xPubMedGoogle ScholarCrossref
    22.
    Min  L, Yoon  W, Mariano  J,  et al.  The Vulnerable Elders-13 survey predicts 5-year functional decline and mortality outcomes in older ambulatory care patients.  J Am Geriatr Soc. 2009;57(11):2070-2076. doi:10.1111/j.1532-5415.2009.02497.xPubMedGoogle ScholarCrossref
    23.
    McDowell  I, Praught  E.  On the measurement of happiness: an examination of the Bradburn scale in the Canada Health Survey.  Am J Epidemiol. 1982;116(6):949-958. doi:10.1093/oxfordjournals.aje.a113497PubMedGoogle ScholarCrossref
    24.
    Bradburn  N.  The Structure of Psychological Well-Being. Chicago, Illinois: Aldine Publishing Co; 1969.
    25.
    Chong  DK.  Measurement of instrumental activities of daily living in stroke.  Stroke. 1995;26(6):1119-1122. doi:10.1161/01.STR.26.6.1119PubMedGoogle ScholarCrossref
    26.
    Lawton  MP, Brody  EM.  Assessment of older people: self-maintaining and instrumental activities of daily living.  Gerontologist. 1969;9(3):179-186. doi:10.1093/geront/9.3_Part_1.179PubMedGoogle ScholarCrossref
    27.
    Aaronson  NK, Ahmedzai  S, Bergman  B,  et al.  The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology.  J Natl Cancer Inst. 1993;85(5):365-376. doi:10.1093/jnci/85.5.365PubMedGoogle ScholarCrossref
    28.
    Sheikh  J, Yesavage  J.  Geriatric Depression Scale (GDS): recent evidence and development of a shorter version.  Clin Gerontol. 1986;5:165-173. doi:10.1300/J018v05n01_09Google ScholarCrossref
    29.
    Mitchell  AJ, Bird  V, Rizzo  M, Meader  N.  Diagnostic validity and added value of the Geriatric Depression Scale for depression in primary care: a meta-analysis of GDS30 and GDS15.  J Affect Disord. 2010;125(1-3):10-17. doi:10.1016/j.jad.2009.08.019PubMedGoogle ScholarCrossref
    30.
    Fried  LP, Tangen  CM, Walston  J,  et al; Cardiovascular Health Study Collaborative Research Group.  Frailty in older adults: evidence for a phenotype.  J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-M156. doi:10.1093/gerona/56.3.M146PubMedGoogle ScholarCrossref
    31.
    Makary  MA, Segev  DL, Pronovost  PJ,  et al.  Frailty as a predictor of surgical outcomes in older patients.  J Am Coll Surg. 2010;210(6):901-908. doi:10.1016/j.jamcollsurg.2010.01.028PubMedGoogle ScholarCrossref
    32.
    O’Connor  AM.  Validation of a decisional conflict scale.  Med Decis Making. 1995;15(1):25-30. doi:10.1177/0272989X9501500105PubMedGoogle ScholarCrossref
    33.
    Cannady  SB, Hatten  KM, Bur  AM,  et al.  Use of free tissue transfer in head and neck cancer surgery and risk of overall and serious complication(s): an American College of Surgeons–National Surgical Quality Improvement Project analysis of free tissue transfer to the head and neck.  Head Neck. 2017;39(4):702-707. doi:10.1002/hed.24669PubMedGoogle ScholarCrossref
    34.
    Jain  U, Somerville  J, Saha  S,  et al.  Predictors of adverse events after neck dissection: an analysis of the 2006-2011 National Surgical Quality Improvement Program (NSQIP) database.  Ear Nose Throat J. 2017;96(2):E37-E45. doi:10.1177/014556131709600218PubMedGoogle ScholarCrossref
    35.
    Schwam  ZG, Sosa  JA, Roman  S, Judson  BL.  Complications and mortality following surgery for oral cavity cancer: analysis of 408 cases.  Laryngoscope. 2015;125(8):1869-1873. doi:10.1002/lary.25328PubMedGoogle ScholarCrossref
    36.
    Derks  W, De Leeuw  R, Winnubst  J, Hordijk  GJ.  Elderly patients with head and neck cancer: physical, social and psychological aspects after 1 year.  Acta Otolaryngol. 2004;124(4):509-514. doi:10.1080/00016480310000656PubMedGoogle ScholarCrossref
    37.
    Moubayed  SP, Sampalis  JS, Ayad  T,  et al.  Predicting depression and quality of life among long-term head and neck cancer survivors.  Otolaryngol Head Neck Surg. 2015;152(1):91-97. doi:10.1177/0194599814557772PubMedGoogle ScholarCrossref
    38.
    Lydiatt  WM, Bessette  D, Schmid  KK, Sayles  H, Burke  WJ.  Prevention of depression with escitalopram in patients undergoing treatment for head and neck cancer: randomized, double-blind, placebo-controlled clinical trial.  JAMA Otolaryngol Head Neck Surg. 2013;139(7):678-686. doi:10.1001/jamaoto.2013.3371PubMedGoogle Scholar
    39.
    Martinez  KA, Li  Y, Resnicow  K, Graff  JJ, Hamilton  AS, Hawley  ST.  Decision regret following treatment for localized breast cancer: is regret stable over time?  Med Decis Making. 2015;35(4):446-457. doi:10.1177/0272989X14564432PubMedGoogle ScholarCrossref
    40.
    Puts  MTE, Hsu  T, Mariano  C,  et al.  Clinical and cost-effectiveness of a comprehensive geriatric assessment and management for Canadian elders with cancer—the 5C study: a study protocol for a randomised controlled phase III trial.  BMJ Open. 2019;9(5):e024485. doi:10.1136/bmjopen-2018-024485PubMedGoogle ScholarCrossref
    41.
    Puts  MTE, Strohschein  FJ, Del Giudice  ME,  et al.  Role of the geriatrician, primary care practitioner, nurses, and collaboration with oncologists during cancer treatment delivery for older adults: a narrative review of the literature.  J Geriatr Oncol. 2018;9(4):398-404. doi:10.1016/j.jgo.2018.04.008PubMedGoogle ScholarCrossref
    42.
    Bagayogo  FF, Lepage  A, Denis  JL, Lamothe  L, Lapointe  L, Vedel  I.  Factors influencing cancer specialists’ decision to collaborate with geriatricians in treating older cancer patients.  Age Ageing. 2016;45(5):723-726. doi:10.1093/ageing/afw101PubMedGoogle ScholarCrossref
    43.
    Shuman  AG, Korc-Grodzicki  B, Shklar  V, Palmer  F, Shah  JP, Patel  SG.  A new care paradigm in geriatric head and neck surgical oncology.  J Surg Oncol. 2013;108(3):187-191. doi:10.1002/jso.23370PubMedGoogle ScholarCrossref
    44.
    Birrer  RB, Vemuri  SP.  Depression in later life: a diagnostic and therapeutic challenge.  Am Fam Physician. 2004;69(10):2375-2382.PubMedGoogle Scholar
    45.
    de Graeff  A, de Leeuw  JR, Ros  WJ, Hordijk  GJ, Blijham  GH, Winnubst  JA.  Long-term quality of life of patients with head and neck cancer.  Laryngoscope. 2000;110(1):98-106. doi:10.1097/00005537-200001000-00018PubMedGoogle ScholarCrossref
    46.
    Bui  AT, Yong Ji  KS, Pham  CT, Le  KM, Tong  TX, Lee  WT.  Longitudinal evaluation of quality of life in laryngeal cancer patients treated with surgery.  Int J Surg. 2018;58:65-70. doi:10.1016/j.ijsu.2018.09.011PubMedGoogle ScholarCrossref
    47.
    Diefenbach  MA, Mohamed  NE.  Regret of treatment decision and its association with disease-specific quality of life following prostate cancer treatment.  Cancer Invest. 2007;25(6):449-457. doi:10.1080/07357900701359460PubMedGoogle ScholarCrossref
    48.
    Hurwitz  LM, Cullen  J, Kim  DJ,  et al.  Longitudinal regret after treatment for low- and intermediate-risk prostate cancer.  Cancer. 2017;123(21):4252-4258. doi:10.1002/cncr.30841PubMedGoogle ScholarCrossref
    49.
    Lavery  HJ, Levinson  AW, Hobbs  AR,  et al.  Baseline functional status may predict decisional regret following robotic prostatectomy.  J Urol. 2012;188(6):2213-2218. doi:10.1016/j.juro.2012.08.016PubMedGoogle ScholarCrossref
    ×