|Year : 2015 | Volume
| Issue : 1 | Page : 94-97
Developing a comprehensive cancer specific geriatric assessment tool
S Rao, N Salins, J Deodhar, M Muckaden
Department of Palliative Medicine, Tata Memorial Hospital, Mumbai, Maharashtra, India
|Date of Web Publication||3-Feb-2016|
Department of Palliative Medicine, Tata Memorial Hospital, Mumbai, Maharashtra
Source of Support: None, Conflict of Interest: None
Background: Population aging is one of the most distinctive demographic events of this century. United Nations projections suggest that the number of older persons is expected to increase by more than double from 841 million in 2013 to >2 billion by 2050. It is estimated that 60% of the elderly patients may be affected by cancer and may present in the advanced stage. The aim of this paper was to develop a brief cancer-specific comprehensive geriatric assessment tool for use in a geriatric population with advanced cancer that would identify the various medical, psychosocial, and functional issues in the older person.Methods: Literature on assessment of geriatric needs in an oncology setting was reviewed such that validated tools on specific domains were identified and utilized. The domains addressed were socioeconomic, physical symptoms, comorbidity, functional status, psychological status, social support, cognition, nutritional status and spiritual issues. Validated tools identified were Kuppuswamy scale (socioeconomic), Edmonton Symptom Assessment Scale (Physical symptoms) and SAKK cancer-specific geriatric assessment tool, which included six standard geriatric measures covering five geriatric domains (comorbidity, functional status, psychological status, social support, cognition, nutritional status). The individual measures were brief, reliable, and valid and could be administered by the interviewer.Conclusion: The tool was developed for use under the geriatric palliative care project of the department of palliative medicine at Tata Memorial Hospital, Mumbai. We plan to test the feasibility of the tool in our palliative care set-up, conduct a needs assessment study and based on the needs assessment outcome institute a comprehensive geriatric palliative care project and reassess outcomes.
Keywords: Advanced cancer, geriatric assessment tool, palliative care
|How to cite this article:|
Rao S, Salins N, Deodhar J, Muckaden M. Developing a comprehensive cancer specific geriatric assessment tool. Indian J Cancer 2015;52:94-7
| » Introduction|| |
United Nations projections suggest that the number of older persons is expected to increase by more than double from 841 million in 2013 to >2 billion by 2050. India has about 100 million elderly at present, and this is expected to increase to 324 million by 2050, constituting 20% of the total population. Cancer is 11 times more likely to develop in people over 65 years as compared to their younger counterparts. In the United States, 60% of all cancers and approximately 70% of cancer-related deaths  occur in those 65 years or older. Based on an Indian Council of Medical Research population-based cancer registry report the prevalence of cancer patients in India above the age of 60 is estimated to reach >1 million by 2021. Government of India adopted the “National Policy on Older Persons” in January 1999 defining senior citizen or elderly as a person who is of age 60 or above. Thus for the purpose of this paper the age 60 years or above will be considered as elderly.
Elderly patients needing palliative care services present with unique concerns and the traditional assessment and management guidelines fail to address their complex needs. The aim of this paper was to develop a brief cancer-specific comprehensive geriatric assessment tool for use in geriatric population in an advanced cancer care set-up that would identify the various medical, psychosocial, and functional issues in the older person.
| » Background and Rationale|| |
Review of literature in geriatrics and oncology indicate that the elderly patients have multiple issues involving various domains that is, physical, cognitive, affective, social, financial, environmental and spiritual that affect their global health.
Pain occurs in nearly all patients with advanced cancer  and is twofold higher in those over the age of 60 or above., Elderly patients in addition have chronic nonmalignant pain that predate cancer. Expression of pain in the elderly patients may be atypical and presence of cognitive impairment, delirium and dementia create barriers in effective pain assessment. Misconceptions about cancer and aging process as well as cultural aversion to narcotics, concerns about side effects and fear of addiction to opioids  further impede effective pain management. Besides pain, a high prevalence of symptoms such as fatigue (up to 70% of elderly patients), loss of appetite and depression has been reported in elderly patients with advanced cancer. Unrelieved or sub-optimally treated symptoms have a serious effect on the quality of life of the elderly  resulting in depression, social isolation, and immobility. The elderly population have multiple comorbidities that affect the outcomes in patients with cancer , and in Indian elderly population an added burden of communicable diseases compound this problem. In addition, the elderly patients are at an increased risk of drug-drug and drug-disease interactions. Frailty, functional status  and malnutrition  are crucial factors that need to be taken into consideration in the care of older adults as it is a strong predictor of negative outcomes including disability, institutionalization, and mortality. A study conducted in a tertiary care hospital in India identified poor nutritional status among elderly cancer patients. The prevalence of depression in cancer ranges from 17% to 25% and has been correlated with decreased quality of life and is a significant predictor of mortality. Suicide is another major concern in older adults almost twice as likely as the younger populations. Cognitive impairments, delirium and dementia have been identified as independent prognostic indicators of survival  in patients with cancer. Lower socioeconomic status has an adverse effect on survival due its effect on nutrition, social support, and lack of access to better disease modifying options. In India problems of the elderly patients are further compounded by factors like lack of social security and inadequate facilities for health care, rehabilitation, and recreation. Major proportion of the elderly patients are out of workforce and partially or totally dependent on others. Social isolation is also an independent predictor of mortality in the geriatric population.
An audit conducted as part of a geriatric palliative care project over 6 months (October 2013–March 2014) by the Department of Palliative Medicine, Tata Memorial Hospital, India indicate that nearly 40% of all patients with advanced cancer referred to palliative care services were aged 60 years or above. The most common physical symptoms reported were pain (74%), fatigue (90%), loss of appetite (75%) and anxiety (45%) as reported on the Edmonton Symptom Assessment Scale. About 68% of the elderly patients complained of mobility impairment with 58% having an Eastern Cooperative Oncology Group-Performance Status of 2 or 3. However, no details regarding patient's baseline level of functioning that is, ability to complete Activities of Daily Living (ADLs) and instrumental activities of daily living (IADLs) were available. Cognitive impairment, perceived social support, presence of psychological and spiritual concerns, nutritional status were not being assessed adequately in a busy palliative care outpatient set-up highlighting the need for a comprehensive geriatric assessment.
A meta-analysis of 28 controlled trials of comprehensive geriatric assessment demonstrated that geriatric assessments if linked with geriatric interventions reduce re-hospitalizations and mortality in older patients through early identification and treatment of problems, reduce functional decline and improve mental health outcomes. However, these tools are time-consuming and impractical for use in a busy palliative care setting. Our goal was to develop a brief and comprehensive assessment tool that could be used in the geriatric population in an advanced cancer care and palliative care setting, which would include all the essential domains evaluated by geriatricians and oncologists as independent predictors of mortality and morbidity in older patients. Following are the validated tools used in of the geriatric population addressing the above-mentioned domains.
| » Measurements|| |
Modified Kuppuswamy's Socioeconomic Status Scale (2013)
Kuppuswamy's scale is widely used to measure the socioeconomic status of an individual in an urban Indian community based on three variables namely education level of head of family (HOF), occupation of HOF and income per month. It is an important tool in hospital and community-based research in India, which was originally proposed in 1976. Socioeconomic status on this study was scored using the updated version of the scale.
Edmonton symptom assessment system
This tool is designed to assist in the assessment of nine symptoms common in cancer patients: Pain, tiredness, nausea, loss of appetite, shortness of breath, drowsiness, depression, anxiety, best wellbeing and others. It is the patient's opinion of the severity of the symptom and the gold standard for symptom assessment.
Charlson comorbidity index
Charlson comorbidity index (CCI) assesses comorbidity level by taking into account both the number and severity of 19 pre-defined comorbid conditions. The CCI was further adapted to account for increasing age by adding one point to the CCI score for each decade of life over the age of 50. Hall (William H Hall, 2004) et al. have created a Microsoft Excel Macro to calculate CCI to facilitate its correct and uniform use in medical research that was used to assess comorbidity in this study. Has good reliability, excellent correlation with mortality and progression-free survival outcomes, and is easily modifiable particularly to account for the effect of age.
Vulnerable elders survey-13
Vulnerable elders survey (VES-13) is a validated tool used to assess the risk of health deterioration in community-dwelling older adults by considering a number of factors including disabilities, age, self-reported health status, and functional limitations. The VES-13 correlates with the Comprehensive Geriatric Assessment with a value of 0.4 and with ADL/IADL scales with a value of 0.5 showing it as a valid tool. Internal consistency for the VES-13 in a study by Luciani et al. found a Cronbach's alpha of 0.9 when compared against Comprehensive Geriatric Assessment (CGA). Sensitivity was reported to be 87% and specificity of 62% versus CGA and 90% and 70% versus ADL/IADL.
Number of falls in the last 6 months
Older patients are at a risk of falls due to mobility, balance, and gait impairments. Patients with cancer are at a greater risk for pathologic fracture or hemorrhage.
Geriatric depression scale-5
The Geriatric depression scale (GDS) was specifically developed for use with older people, 60 years and above, as a basic screening measure for depression. Holy and colleagues selected 5 items that had the strongest correlation with a clinical diagnosis of depression and developed the GDS-5 for use in faster paced settings. Sensitivity of GDS-5 ranges from 89% to 98% and specificity ranges from 73% to 85% (Rinaldi et al. 2003; Weeks et al. 2003). Reliability coefficient was 0.84, and interrater reliability was 0.88 (Rinaldi et al. 2003).
The Modified Medical Outcomes Study Social Support Survey
To reduce respondent burden the original 19-item Medical Outcomes Study Social Support Survey  was shorted to an 8-item version named modified Medical Outcomes Study Social Support Survey (mMOS-SS)., The mMOS-SS has two subscales covering two domains (emotional and instrumental (tangible) social support). Moser et al. demonstrated that the mMOS-SS demonstrated good internal reliability, consistent factor structure, good convergent, divergent and discriminate validity. It's a reliable and valid tool to measure social support especially in the geriatric context.
This is a simple screening tool developed in 2000 to detect cognitive impairment quickly in older adults. It comprises of 3-item recall test and clock drawing test, which allows clinicians to quickly assess numerous cognitive domains and provides a visible record of both normal and impaired performance that can be tracked over time. In the original validation article, with a sample of culturally diverse, community-dwelling persons, 50% of whom had dementia, the Mini-Cog demonstrated a sensitivity of 99% and specificity of 96%, compared with Mini Mental State Examination (91% and 92% respectively). A score of 3–5 out of 5 is a negative screen for dementia (Borson et al., 2006), but a score of 0–2 out of 5 may increase detection of mild cognitive impairment (McCarten et al., 2012). The Mini-Cog is not strongly influenced by education, culture, or language, and it was perceived as less stressful to the patient than other longer mental status tests.
Mini-Nutritional assessment Short Form
The Mini-Nutritional assessment (MNA) - Short Form is a quick screening version of the original MNA used to identify older adults at risk for malnourishment early so that nutritional intervention can be initiated. The sensitivity has been reported as 97.9% and specificity 100% for predicting under-nutrition, diagnostic accuracy 98.7%, reliability not reported.
We screened the spiritual concerns using the two-question model developed by Fitchett and Risk. The two questions included:
- Is spirituality or religion important to you
- Are your spiritual resources working for you?
| » Conclusion|| |
Geriatric patients with advanced cancer present with a unique set of needs and challenges and the prevailing adult palliative care needs assessment model fails to recognize these distinctive domains. Any assessment that does not address the special needs of the elderly would be incomplete and inappropriate. An effective geriatric palliative care program should evaluate the physiologic, functional, and health-related quality of life of the patient; aid in formulating appropriate treatment and management strategies; monitor the clinical and functional outcomes; and in addition aid in identifying patient and caregiver treatment preferences.
Department of Palliative Medicine at Tata Memorial Hospital, Mumbai, developed this tool, as an attempt to bridge gaps in needs assessment such that it will positively improve geriatric palliative care services and thereby improve outcomes. We plan to assess the feasibility of the tool, validate it in regional language, conduct a needs assessment study, and based on the needs assessment outcomes, institute a comprehensive geriatric palliative care package and reassess outcomes of intervention.
| » References|| |
Howlader N, Noone AM, Krapcho M, Neyman N, Aminou R, Waldron W, et al
. SEER Cancer Statistics Review 1975-2009 (Vintage 2009 Populations), National Cancer Institute, Bethesda, MD. Available from: http://www.seer.cancer.gov/csr/1975_2009_pops09/
Edwards BK, Howe HL, Ries LA, Thun MJ, Rosenberg HM, Yancik R, et al.
Annual report to the nation on the status of cancer, 1973-1999, featuring implications of age and aging on U.S. cancer burden. Cancer 2002;94:2766-92.
ICMR Population Based Cancer Registry Reports-2 Year Report. Natl Cancer Regist Progr 2004-2005.
Fields HL, Dubner R, Cervero F, eds, Bonica JJ. Treatment of cancer pain: Current status and future needs. Adv Pain Res Ther 1985;9:589-616.
Crook J, Rideout E, Browne G. The prevalence of pain complaints in a general population. Pain 1984;18:299-314.
Lavsky-Shulan M, Wallace RB, Kohout FJ, Lemke JH, Morris MC, Smith IM. Prevalence and functional correlates of low back pain in the elderly: The Iowa 65+Rural Health Study. J Am Geriatr Soc 1985;33:23-8.
Sengstaken EA, King SA. The problems of pain and its detection among geriatric nursing home residents. J Am Geriatr Soc 1993;41:541-4.
Lamberg L. Chronic pain linked with poor sleep: Exploration of causes and treatment. JAMA 1999; 281:691-2.
Giacalone A, Quitadamo D, Zanet E, Berretta M, Spina M, Tirelli U. Cancer-related fatigue in the elderly. Support Care Cancer 2013;21:2899-911.
Allard P, Maunsell E, Labbé J, Dorval M. Educational interventions to improve cancer pain control: A systematic review. J Palliat Med 2001;4:191-203.
Cavalieri TA. Pain management in the elderly. J Am Osteopath Assoc 2002;102:481-5.
Extermann M, Balducci L, Lyman GH. What threshold for adjuvant therapy in older breast cancer patients? J Clin Oncol 2000;18:1709-17.
Firat S, Bousamra M, Gore E, Byhardt RW. Comorbidity and KPS are independent prognostic factors in stage I non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 2002; 52:1047-57.
Reddy PH. The health of the aged in India. Health Transit Rev 1996; 6 Suppl: 233-44.
Jacox A, Carr DB, Payne R, et al
. Management of cancer pain. Clinical Practise Guideline Number 9. Rockville, MD: Agency for Health Care Policy and Research, US Department of Health and Human Services, March 1994; AHCPR Publication No. 94-0592.
Van Iersel MB, Rikkert MG. Frailty criteria give heterogeneous results when applied in clinical practice. J Am Geriatr Soc 2006;54:728-9.
Extermann M, Overcash J, Lyman GH, Parr J, Balducci L. Comorbidity and functional status are independent in older cancer patients. J Clin Oncol 1998;16:1582-7.
Newman AB, Yanez D, Harris T, Duxbury A, Enright PL, Fried LP, et al.
Weight change in old age and its association with mortality. J Am Geriatr Soc 2001;49:1309-18.
Chakravarty C, Hazarika B, Goswami L, Ramasubban S. Prevalence of malnutrition in a tertiary care hospital in India. Indian J Crit Care Med 2013;17:170-3.
Massie MJ. Prevalence of depression in patients with cancer. J Natl Cancer Inst Monogr 2004;32: 57-71.
Satin JR, Linden W, Phillips MJ. Depression as a predictor of disease progression and mortality in cancer patients: A meta-analysis. Cancer 2009;115:5349-61.
Miniño AM, Arias E, Kochanek KD, Murphy SL, Smith BL. Deaths: Final data for 2000. Natl Vital Stat Rep 2002;50:1-119.
Wolfson C, Wolfson DB, Asgharian M, M'Lan CE, Ostbye T, Rockwood K, et al.
A reevaluation of the duration of survival after the onset of dementia. N Engl J Med 2001;344:1111-6.
Ingle GK, Nath A. Geriatric health in India: Concerns and solutions. Indian J Community Med 2008;33:214-8.
Chandwani H, Jivarajani P, Jivarajani H. Health and social problems of geriatric population in an urban setting of Gujarat, India. Internet J Geriatr Gerontol 2008;5:1.
Seeman TE, Berkman LF, Kohout F, Lacroix A, Glynn R, Blazer D. Intercommunity variations in the association between social ties and mortality in the elderly. A comparative analysis of three communities. Ann Epidemiol 1993;3:325-35.
Stuck AE, Siu AL, Wieland GD, Adams J, Rubenstein LZ. Comprehensive geriatric assessment: A meta-analysis of controlled trials. Lancet 1993;342:1032-6.
Cohen HJ, Feussner JR, Weinberger M, Carnes M, Hamdy RC, Hsieh F, et al.
A controlled trial of inpatient and outpatient geriatric evaluation and management. N Engl J Med 2002;346:905-12.
Carreca I, Balducci L, Extermann M. Cancer in the older person. Cancer Treat Rev 2005;31:380-402.
SR Dudala. Updated Kuppuswamy's socioeconomic scale for 2012. J NTR Univ Health Sci 2013;2:201-2.
Bruera E, Kuehn N, Miller MJ, Selmser P, Macmillan K. The Edmonton Symptom Assessment System (ESAS): A simple method for the assessment of palliative care patients. J Palliat Care 1991;7:6-9.
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987;40:373-83.
Saliba D, Elliott M, Rubenstein LZ, Solomon DH, Young RT, Kamberg CJ, et al.
The Vulnerable Elders Survey: A tool for identifying vulnerable older people in the community. J Am Geriatr Soc 2001;49:1691-9.
Naeim A, Reuben D. Geriatric syndromes and assessment in older cancer patients. Oncology (Williston Park) 2001;15:1567-77, 80.
Rinaldi P, Mecocci P, Benedetti C, Ercolani S, Bregnocchi M, Menculini G, et al.
Validation of the five-item geriatric depression scale in elderly subjects in three different settings. J Am Geriatr Soc 2003;51:694-8.
Moser A, Stuck AE, Silliman RA, Ganz PA, Clough-Gorr KM. The eight-item modified Medical Outcomes Study Social Support Survey: Psychometric evaluation showed excellent performance. J Clin Epidemiol 2012;65:1107-16.
Vellas B, Villars H, Abellan G, Soto ME, Rolland Y, Guigoz Y, et al.
Overview of the MNA – Its history and challenges. J Nutr Health Aging 2006;10:456-63.
Borson S, Scanlan JM, Chen P, Ganguli M. The Mini-Cog as a screen for dementia: Validation in a population-based sample. J Am Geriatr Soc 2003;51:1451-4.
Vijaya K, Ravikiran E. Kuppuswamy's socio-economic status scale-updating income ranges for the year 2013. Natl J Res Community Med 2013;2:79-148.
Extermann M. Measuring comorbidity in older cancer patients. Eur J Cancer 2000;36:453-71.
Hays RD, Sherbourne CD, Mazel RM. User's Manual for Medical Outcomes Study (MOS) Core Measures of Health-Related Quality of Life. St. Monica: CA Rand; 1995.
Clough-Gorr KM, Ganz PA, Silliman RA. Older breast cancer survivors: Factors associated with change in emotional well-being. J Clin Oncol 2007;25:1334-40.
Ganz PA, Guadagnoli E, Landrum MB, Lash TL, Rakowski W, Silliman RA. Breast cancer in older women: Quality of life and psychosocial adjustment in the 15 months after diagnosis. J Clin Oncol 2003;21:4027-33.
Del Ser T, McKeith I, Anand R, Cicin-Sain A, Ferrara R, Spiegel R. The mini-cog: A cognitive “vital signs” measure for dementia screening in multi-lingual elderly. Int J Geriatr Psychiatry 2000;15:1021-7.
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