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Table of Contents
ORIGINAL ARTICLE: GERIATRIC ONCOLOGY SECTION
Year : 2021  |  Volume : 4  |  Issue : 4  |  Page : 656-662

Utilization of technology among older Indian patients with cancer: A cross-sectional study


1 Department of Medical Oncology, Tata Memorial Hospital, Mumbai, Maharashtra, India
2 Department of Clinical Pharmacology, Advanced Centre for Treatment Research and Education in Cancer, Mumbai, Maharashtra, India
3 Department of Surgical Oncology, Tata Memorial Hospital, Mumbai, Maharashtra, India

Date of Submission15-Nov-2021
Date of Decision27-Nov-2021
Date of Acceptance09-Dec-2021
Date of Web Publication29-Dec-2021

Correspondence Address:
Kumar Prabhash
Department of Medical Oncology, Tata Memorial Hospital, Parel, Mumbai - 400 012, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/crst.crst_290_21

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  Abstract 


Background: Technology has advanced tremendously and can address the gaps in the care of older adults with cancer. Studies from high-income countries reveal that the use of technology among older adults is on the rise, but there are no published data regarding the use of technology by health-seeking older adults from India.
Objectives: We aimed to assess the use of mobile phones, Internet, and social media applications among older adults with cancer attending a geriatric oncology clinic. We also aimed to study their association with various intrinsic factors.
Materials and Methods: This cross-sectional study was conducted in the geriatric oncology clinic at the Tata Memorial Hospital, a tertiary care center in Mumbai, India, between April 2021 and October 2021. Participants were patients with cancer aged 60 years and over, who were referred to the geriatric oncology clinic. Clinicodemographic details were recorded, and a multi-dimensional geriatric assessment was performed. Patients were asked whether they owned and used mobile phones, Internet, E-mail, and social media applications such as WhatsApp and Facebook. The same questions regarding technology use were asked to their accompanying caregivers. Categorical variables were compared using the Fisher's exact and Pearson's Chi-squared test.
Results: A total of 309 participants were included. The median age was 68 (interquartile range, 64–72) years; 262 (85%) participants were aged <75 years. There were 234 (76%) men in the cohort. A total of 25 (33%) women and 25 (11%) men were uneducated; 225 (81%) participants had mobile phones; and 24 (9%) had mobile phones and landlines. Female patients (59% vs. 77%, P = 0.001) and those with poor vision (67% vs. 80%, P = 0.036), no education (50% vs. 74%, P < 0.001), and impaired cognition (49% vs. 84%, P < 0.001) were less likely to own a mobile phone. A total of 70 (25%) participants reported that they accessed the Internet, but only 16 (6%) used Internet, E-mail, and social media on their own phones. Use of the Internet and social media was less likely among people with no education ([4% vs. 22%, P < 0.001] and [6% vs. 21%, P < 0.01], respectively) and impaired cognition ([5% vs. 26%, P = 0.013] and [8% vs. 28%, P = 0.022], respectively). Among accompanying caregivers, 297 (99%) reported that they used mobile phones, while 223 (75%) used E-mail and social media applications.
Conclusion: Over 80% of older Indian adults with cancer use mobile phones, but only 25% use Internet and social media. Women and those with no education, poor vision, and impaired cognition are less likely to own a mobile phone. People with no education and impaired cognition are also less likely to use Internet and social media. Further studies are required to understand the acceptance rate and feasibility of technology use in our setting and to gather more evidence for the effectiveness of these interventions.

Keywords: Cancer, geriatric oncology, older adults, technology


How to cite this article:
Rao AR, Gattani S, Castelino R, Kumar S, Dhekale R, Krishnamurthy J, Ramaswamy A, Noronha V, Gota V, Banavali S, Badwe RA, Prabhash K. Utilization of technology among older Indian patients with cancer: A cross-sectional study. Cancer Res Stat Treat 2021;4:656-62

How to cite this URL:
Rao AR, Gattani S, Castelino R, Kumar S, Dhekale R, Krishnamurthy J, Ramaswamy A, Noronha V, Gota V, Banavali S, Badwe RA, Prabhash K. Utilization of technology among older Indian patients with cancer: A cross-sectional study. Cancer Res Stat Treat [serial online] 2021 [cited 2022 Jan 20];4:656-62. Available from: https://www.crstonline.com/text.asp?2021/4/4/656/334225




  Introduction Top


It is apparent that cancer is primarily a disease of the aging population.[1] Geriatric assessment (GA), a multi-dimensional and multi-disciplinary assessment of older adults, is the gold standard for assessing the robustness of older adults with cancer.[2] It helps in identifying individuals who are at a greater risk of chemotoxicity, early surgical complications,[3] re-admission, and early mortality.[4] The American Society of Clinical Oncology and other organizations and societies recommend the implementation of GA at each phase of cancer care.[5],[6]

Despite the well-known benefits of GA and GA-guided interventions, the resources and time required to integrate GA into clinical practice remain principal barriers in its implementation. The assessment primarily happens in the outpatient department, and even during chemotherapy, patients spend little time in the clinics. Older adults spend most of their time at home, and this is when symptoms of complications and adverse effects from medical treatment are likely to occur.

Information technology, mainly wireless and web-based technology, has advanced tremendously. Health information technologies can mitigate the gaps in the care of older adults with cancer. Digital health technology[7] includes many platforms, such as web- or application-based electronic patient-reported outcomes, remote monitoring tools, and sensors and wearables. Online communities are also suitable for providing and receiving social support.[8] The impact of applied technologies can be categorized as accessible communication, emergency assistance, physical well-being, and mental well-being.[9]

Studies from other countries indicate that although the use of technology among older adults is increasing, it lags behind that of young adults. The National Health and Aging Trends Study revealed that 64% and 76% of older adults used computers and cellphones, respectively.[10] A study among cancer survivors reported low electronic health literacy, but 87.6% and 87.5% of participants were reported to use computers and smartphones, respectively.

There are no published data regarding the use of technology by health-seeking older adults from India. We therefore aimed to assess the use of mobile phones, Internet, and social media among older patients with cancer attending the geriatric oncology clinic at our hospital and the association with intrinsic factors such as vision, hearing, cognition, and the presence of geriatric syndromes.


  Materials and Methods Top


General study details

This cross-sectional study was conducted between April 2021 and October 2021 in the geriatric oncology clinic of the Tata Memorial Hospital, a tertiary cancer care center in Mumbai, India. The geriatric oncology clinic is a multi-disciplinary clinic, the members of which convene twice a week in the Outpatient Department of Medical Oncology. Patients undergo a multi-dimensional GA, based on the results of which treatment and follow-up are planned and appropriate recommendations are made. The multi-disciplinary team includes a medical oncologist, clinical pharmacologist, dietician, psychiatrist, social worker, and physiotherapist.[11] The study was approved by the Institutional Ethics Committee (Supplementary Appendix 1). The need to obtain written informed consent was waived for the retrospective portion of the study. The study was conducted according to ethical guidelines established by the Declaration of Helsinki and Good Clinical Practice Guidelines. No funding was used for the study.

Participants

We included adults with cancer aged 60 years and over who had been evaluated in the geriatric oncology clinic and who had answered the technology-related questions. There were no specific exclusion criteria.

Variables

The primary aim of the study was to assess the use of telephones, the type of telephone used (landline, mobile, or both), and the use of Internet and social media among older patients with cancer and their caregivers. We also sought to find out the association of phone/Internet/social media use with intrinsic factors such as age, gender, education, vision, hearing, comorbidities, and cognition.

Study methodology

Participants were interviewed for demographic details, including age, sex, marital status, education, and native state of residence. The state of residence was categorized based on geographical location in India into north, north-east, central, western, and southern states. Clinical assessment included distant and near vision assessment using the Snellen and Jaeger charts, respectively. Visual ability was categorized as vision not impaired, good corrected vision with glasses, poor vision even with glasses, and poor vision but no glasses. Hearing screening was performed using a single question, “Do you have difficulty hearing?” We also assessed the degree of handicap due to hearing impairment using the Hearing Handicap Inventory. A score of 6 or more indicates impaired hearing. Basic and instrumental activities of daily living were assessed using the Katz Index of Independence in Activities of Daily Living and Lawton Instrumental Activities of Daily Living, respectively.[12] Scores of <6 in the Katz Index and <8 for women and <5 for men in the Lawton Instrumental Activities Scale were considered as impaired. Cognition of literate and illiterate participants was assessed using the Mini-Mental State Examination (MMSE)[13] and the Hindi-Mental State Examination (HMSE), respectively.[14] Impaired cognition was defined as a score of <24. In addition to performing the GA, the participants were asked whether they owned and used cellphones, Internet, E-mail, and social media applications such as WhatsApp and Facebook. We also asked them if they accessed the Internet services on their phone or on other devices. The caregivers accompanying the patients were also asked the same set of questions.

Statistics

All data were entered and analyzed using the Statistical Package for the Social Sciences (IBM Corp. Released 2015. IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp). No sample size calculation was performed for this study. Categorical variables were described as frequencies and percentages, and qualitative data were expressed as mean, standard deviation, median, and range. Categorical variables such as use of phone, Internet, and social media were compared using Fisher's exact and Pearson's Chi-squared test. P < 0.05 was considered statistically significant.


  Results Top


Respondents

A total of 309 participants were included in the study [Figure 1]. The median age of the participants was 68 years (interquartile range [IQR], 64–72). A total of 262 (85%) participants were aged <75 years, and 234 (76%) were men [Table 1].
Figure 1: Scheme of the inclusion of participants in the study

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Table 1: Descriptive parameters of study participants (n=309)

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In our cohort, 63 (27%) men and 22 (29%) women had impaired hearing and 13 (6%) men and 11 (15%) women had poor vision. The mean MMSE/HMSE score was 25.89 ± 3.55, and 28 (12%) men and 12 (16%) women had impaired cognition. Among comorbidities, hypertension was the most common (44%), followed by diabetes (22%).

Technology use

Among the study participants, 53 (19%) did not own a phone, whereas 225 (81%) had mobile phones [Table 2]. Of the 284 patients who responded to the question regarding Internet use, 70 (25%) participants used the Internet; 60 (21%) participants reported that they used Internet on their own phone, but only 16 (6%) used Internet, E-mail, and social media on their own phone. Regarding social media use, 65 (21%) reported that they used some form of social media. Thirty-two (10%) participants reported that they used WhatsApp alone, and 33 (11%) used WhatsApp and Facebook. Among the caregivers of older adults with cancer, 223 (75%) used E-mail and social networking, while 40 (13%) only used social media.
Table 2: Telephone and social media use among older adults and their caregivers

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The association of age, sex, vision, hearing, state of residence, education, and cognition with the ownership of a phone and use of the Internet and social media is shown in [Table 3]. We found that patients less likely to own a phone included female participants (59% vs. 77%, P = 0.001) and those with poor vision (67% vs. 80%, P = 0.036), no education (50% vs. 74%, P < 0.001), and impaired cognition (49% vs. 84%, P < 0.001). Use of Internet was found to be less likely among participants with no education (4% vs. 22%, P < 0.001) and impaired cognition (5% vs. 26%, P = 0.013). The use of social media was lower among participants with no education (6% vs. 21%, P < 0.01) and impaired cognition (8% vs. 28%, P = 0.022).
Table 3: Association between various patient characteristics and use of technology

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  Discussion Top


In our study, the use of mobile phones was reported by 225 (81%) older Indian adults with cancer. Women and those with poor vision, no education, and impaired cognition were less likely to own a phone. The use of Internet (25%) and social media (21%) was low among the older patients, but high among their caregivers (75%). A substantial proportion of participants used WhatsApp (10%) and Facebook (11%). People with no education and impaired cognition were less likely to use the Internet and social media. Nearly all patient caregivers (99%) used mobile phones, and 86% used some form of social networking. Our study is the first to report the use of technology among older patients with cancer and their caregivers in India. The findings from our study will help guide the planning of telehealth services, and provide a roadmap for harnessing technology to advance the care of this vulnerable cohort.[15]

The median age of the study population was 68 years (IQR, 64–72), and 85% of the participants were aged below 75 years. Our population was older than that of a previous study (mean age, 60.6 ± 11 years), from Canada, conducted among cancer survivors to survey technology literacy.[16] This could be because our study was conducted in a geriatric oncology clinic that caters to people above 60 years of age. Few quantitative and qualitative studies have been conducted among community-dwelling older adults,[17],[18],[19] but there is sparse literature specifically focusing on technology use among older patients with cancer.

We found that 81% of the participants owned a phone. This is similar to the findings reported by a previous study from Greece, which found that 78.3% of the participants used mobile phones,[20] and an unpublished survey from India. Interestingly, in our study, 32% women and 12.4% men reported that they did not own a phone, which was a statistically significant difference (P = 0.001). These findings are similar to previous studies conducted in community settings[21],[22],[23] and national surveys from the West.[20] This is likely to be due to the influence of gender-based life-course trajectories in education, opportunities, and employment.[24] Few studies have reported that women were more likely to use technology to obtain health- and hobby-related information compared to men.[25] Participants with poor vision (67% vs. 80%, P = 0.036), no education (50% vs. 74%, P < 0.001), and impaired cognition (49% vs. 84%, P = 0.013) were significantly less likely to use a phone. These findings suggest that complex cognitive skills, including good vision, are essential for people to be able to use mobile phones. Previous studies have reported that numerous cognitive and physical challenges, such as altered cognition, perception issues, and difficulty hearing or seeing, can hinder the use of technology among older adults.[26],[27]

Over three-quarter of our participants did not use the Internet for social media or E-mail, and 14% of those who used the Internet did not use it on their own phones, and rather depended on another device for access. About 10% of the participants used WhatsApp only, and 11% used both WhatsApp and Facebook. The Internet use among our participants was lower than that reported in other studies (which have reported between 38.6% and 67%).[28],[29] One of these studies was a population-representative survey conducted across Germany and the other was a cross-sectional survey conducted across 13 cities in China; ethnocultural differences could possibly explain the difference in the results. Not surprisingly, illiteracy and impaired cognition were significantly associated with reduced use of the Internet and social media applications. Previous studies have reported that younger age, male sex, higher education levels, higher monthly income, wide social network, high health-related quality of life, lower level of depressive symptoms, and higher rates of chronic illness were associated with greater Internet use.[27],[30] Similary, a national survey among older adults in Singapore reported that male sex, lower education, and limited instrumental activity of daily living experienced difficulties with Internet use.[31] The full extent of the health benefits of technology use among older adults is yet to be explored. A survey from a subset of participants from the health and retirement study reported that technology use is associated with lower incidence of loneliness, fewer chronic illnesses, better health, and lower rates of depression.[32]

In addition to physical and cognitive limitations, other factors which have been shown to hinder the use of technology are lack of access and familiarity, discomfort in seeking assistance, trust issues, and privacy concerns. Nevertheless, nearly 70% of the participants in a study reported that they were open to learning new technology. Moreover, 95% of participants reported that they were somewhat satisfied with the technologies they used for communication;[32] however, they also stated that they found it too expensive, challenging and complicated to learn, and voiced their difficulty in keeping up with changes in technology.

In our study, the use of technology was high among the patients' caregivers; 10% of the caregivers only used mobile phones, 75% used E-mail and social networking applications, and 13% only used social media. These findings mirror the findings reported by the Pew Research Center.[33] Caregivers have different needs and distinct barriers compared to older adults themselves. In dementia, tools that focus on improving the self-efficacy of caregivers can reduce their care burden;[34],[35] however, the effect of caregiver technology interventions has not been consistent.[36],[37],[38] Studies reporting the benefits of interventions to reduce cancer caregiver burden reveal the enormous potential for improvements in cancer caregiver interventions.[39] Caregivers with greater access to and use of technology have been found to be more receptive to technology-based tools to help with their caregiver roles.[40]

Our study assessed the acceptance and use of technology among older Indian patients with cancer and their caregivers. Although the use of Internet and social media applications was low among our patients, the high utilization of technology by the caregivers supports the vision of technology use to provide healthcare at the doorstep.[41] This can include monitoring cancer- and treatment-related adverse effects, monitoring and reporting of vital signs such as blood pressure and weight, providing education, and promoting a healthy lifestyle. Other uses of technology include the establishment of online cancer support groups and electronic administration of the GA, which could help oncologists plan appropriate care and promote the implementation of geriatric oncology services across the country.

Our study is the first from the Indian subcontinent to assess the use of phones, Internet, and social media among older adults attending the geriatric oncology clinic and their caregivers, and whether use varied based on the presence of intrinsic factors such as vision, hearing, and cognition. Our study has several limitations. We did not enquire about factors such as the socio-economic status and place of residence (urban or rural) of the patients, which can hinder technology use. In addition, the willingness to use technology for health benefits was not reported. Moreover, not all the accompanying family members were the primary caregivers of the patients. Our hospital is a tertiary care apex cancer hospital, and many patients travel from their hometowns to seek care at our center. Sometimes, the patients are accompanied by children or persons other than the primary caregiver, who may stay back at the local place to care for the rest of the family. Hence, it cannot be concluded that most primary caregivers of older Indian patients with cancer have access to mobile phones and the Internet. We included only those patients who attended the geriatric oncology clinic in a tertiary cancer center. Hence, the results cannot be generalized to all older adults with cancer in the community.


  Conclusion Top


Nearly 81% of older Indian adults with cancer use mobile phones, but only 25% use Internet services and social media applications. Women and those with no education, poor vision, and impaired cognition are less likely to own a mobile phone. People with no education and impaired cognition are also less likely to use Internet and social media. Further studies are required to understand the acceptance rate and feasibility of technology use in our setting and to gather more evidence for the effectiveness of these interventions.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

Supplementary Appendix

Supplementary Appendix 1: Study protocol

Clinical Study Protocol

Retrospective and prospective analysis of the results of a comprehensive geriatric assessment of older patients with cancer who have been evaluated in the Geriatric Oncology Clinic at Tata Memorial Hospital


  Introduction Top


The world's older population continues to grow at an unprecedented rate. Today, 8.5% of people worldwide (617 million) are aged 65 and over. “An Aging World: 2015” reported that this proportion will increase to almost 17% of the world's population by 2050, or 1.6 billion.[1] According to a 2016 report by the Ministry of Statistics and Programme Implementation, India has 103.9 million elderly (people above age 60 years), about 8.5% of the population. These numbers are based on the 2011 census.[2] In 2018, the government stated in the Parliament that India will have 34 crore people above 60 years of age by 2050, which would be more than the total population of the United States of America.[3] Advancing age is a risk factor for the development of malignancy, with persons over 65 years accounting for 60% of newly diagnosed malignancies and 70% of all cancer deaths, mainly cancers of the breast, lung, prostate, cervix, esophagus, and ovary.[4] It has been predicted that in 2026, in India, there will be approximately 450,000 men and 370,000 women with cancer in the ≥ 60 years age population.[5]

Management of the older patient with cancer is a challenge. These patients have comorbidities, are on multiple medications, are often frail, and may have social, economic, and psychological problems. Many times, the older patients with cancer are not considered for a curative treatment approach, despite the tumor being amenable to radical treatment, just by virtue of their age. Even when these geriatric oncology patients are treated with chemotherapy, radiation, and/or surgery, they may experience more toxicity, and higher chance of morbidity and mortality. Some fit older patients may be denied aggressive therapy for fear of excessive morbidity and some frail older patients may receive therapy that is overly aggressive, leading to morbidity. Striking the right balance is a challenge. Many of the landmark clinical trials have excluded geriatric oncology patients, making the management decision even more difficult.

The American Society of Clinical Oncology[6] and the International Society of Geriatric Oncology (SIOG)[7] have official guidelines that detail the recommended evaluation of an older patient with cancer, and include evaluation for various vulnerabilities, a thorough check of the medications and assessment for the presence of polypharmacy or the presence of potentially inappropriate medications, assessment of the risk of chemotherapy toxicity, and evaluation of the life expectancy. This comprehensive evaluation can be time and resource-consuming and most often, our older patients with cancer at Tata Memorial Hospital are evaluated and treated based on clinician discretion without the use of a comprehensive geriatric assessment (CGA) and without the use of the various standard validated tools.

In order to improve the care of our older patients with cancer, we started the geriatric oncology clinic at Tata Memorial Center on June 15, 2018. We would like to retrospectively and prospectively analyze the data obtained from this geriatric oncology clinic.

Aims and objectives

Primary objective

To describe the profile of the patients evaluated at the geriatric oncology clinic at Tata Memorial Center. This description will include the following:

  1. The incidence of vulnerabilities in the domains of function, falls, comorbidities, social, psychological, cognition, and nutrition
  2. The incidence of polypharmacy and of potentially inappropriate medications.


Secondary objectives

To describe the:

  1. Time taken to perform the CGA
  2. Acceptability and feasibility of the various self-administered questionnaires for our patients
  3. To assess if various short screening tools such as G8, VAS, and TRST can predict for the presence of an abnormality in the CGA
  4. The chemotherapy risk assessment profile of the patients
  5. Quality of life of geriatric oncology patients and caregivers
  6. The prevalence of fatigue, falls, insomnia, constipation, urinary obstruction, and various other symptoms in geriatric oncology patients
  7. To evaluate whether the vulnerabilities of the geriatric oncology patients were recognized and/or addressed during the preceding routine oncology assessment and workup, prior to referral to the geriatric oncology clinic
  8. The prevalence of anemia, hypoalbuminemia, renal dysfunction, hyponatremia, and various other laboratory abnormalities
  9. The ability of the chemotherapy risk assessment calculator to predict actual therapy toxicity in the patients who went on to receive systemic therapy
  10. To evaluate the correlation of the presence of vulnerabilities in the various domains to the development of chemotherapy toxicity
  11. To evaluate the PFS and OS in our geriatric oncology patients
  12. To evaluate the correlation of the presence of vulnerabilities to overall survival
  13. To evaluate the correlation of the presence of polypharmacy and/or potentially inappropriate medications to the development of chemotherapy toxicity and/or overall survival
  14. To evaluate if any other factors such as social factors, laboratory abnormalities, type of primary, tumor stage, and presence of various symptoms such as fatigue may impact on the overall survival.


Inclusion criteria

The inclusion criteria for evaluation in the geriatric oncology clinic are as follows:

  1. Age 60 years and over
  2. Diagnosis of malignancy
  3. ECOG performance status 0–3, i.e., patient not completely disabled.


For the retrospective analysis, we will include all patients whose details have been entered in the prospectively maintained database of the geriatric oncology clinic from June 15, 2018, onward until the date when the IEC approves the study; following this date, we will prospectively analyze the database.

Exclusion criteria

The only exclusion criterion for evaluation in the geriatric oncology clinic is patient or caregiver refusal to undergo assessment.


  Methods Top


The geriatric oncology clinic was started on June 15, 2018, and was held once a week in the Outpatient Department of Medical Oncology at Tata Memorial Hospital, Parel, Mumbai. The study will be divided into two portions – the retrospective portion will consist of the details of the patients who have already undergone evaluation in the geriatric oncology clinic. Once the IEC grants approval, the second portion of the study, i.e., the prospective portion, will start, in which patients will be prospectively evaluated and the data will be analyzed after obtaining written informed consent.

Patients will undergo a CGA and the information was prospectively entered into a Microsoft Excel sheet. For the first portion of the study, there was no written informed consent for being evaluated in the geriatric clinic; however, verbal consent was obtained. Once IEC approval is obtained, the second prospective portion of the study will begin, and the data will be collected prospectively in a database, after obtaining written informed consent.

Process of geriatric assessment: Patients will be explained the need for a geriatric assessment and will be asked if they were willing to proceed. Written informed consent will be obtained if patient is willing to participate. The assessment will be carried out by one to three (depending on availability) medical oncologists with the help of a social worker. We will follow the ASCO and SIOG guidelines for CGA.[6],[7] Patients will be interviewed, asked to fill out the various questionnaires (help will be provided by the oncologist or the social worker, if necessary), timed get-up-and-go will be checked in the clinic room, and height, weight, mid-arm, and mid-thigh circumference will be measured. Disease-related and treatment-related information will be obtained from the electronic medical records. Patients will fill out the quality of life (QOL) form (EORTC QLQ C30) and caregivers who were willing will fill out the Caregiver Burden Scale. No additional testing either blood tests or imaging will be done. The details of the results of the geriatric assessment will be made available to the patient's treating oncologists through the electronic medical records along with recommendations for possible interventions to tackle vulnerabilities in non-oncologic problem areas. In patients who are noted to have deficits in functions or history of falls, referral will be made to the physiotherapy and occupational therapy department. Similarly, patients with deficits in nutrition or depression/anxiety will be referred to the dietitian and to the psychiatrist/counselor, respectively. No change in oncologic management of the patient will be made. The time taken for the assessment will be recorded; however, this will not include the time spent by the patient filling out the self-administered questionnaires for ADL, IADL, GDS-Short Form, GAD-7, OARS-MSS or MOS-SSS, and QOL forms and the time spent assessing the MNA by the social worker.

Domains assessed: We will record the patient's demographic details (age, gender, education, address, living situation and number of caregivers, profession, and smoking history) and disease-related features (primary tumor, stage, intent of therapy, and therapy planned). We will document the medications that the patient is taking, both prescription and over-the-counter, including the use of alternative medicines (Ayurvedic/Homeopathic/Naturopathic/other), and the use of potentially inappropriate medicines as per Beers criteria.[8] We will ask the patients about the presence of symptoms such as insomnia, constipation, falls, fatigue (fatigue was quantified using the MOB-T and MOB-H scales),[9] urinary incontinence, acidity/gastric ulcers, and the presence of sensory deficits such as vision/hearing impairment.

In the retrospective portion of the study, not all domains were assessed in all patients. Our understanding of the process of a CGA evolved with time and we added/changed assessments. We will assess the following domains:

  1. Function: We will document the ECOG performance status, activities of daily living (Katz Index of Independence in Activities of Daily Living),[10] IADL (Lawton Scale),[11] and one performance-based measure of mobility (Timed-Up-and-Go test, TUG, in which the patient will be asked to sit in a chair, the timer will be started, and the patient will be asked to get up, walk a distance of 3 m, turn around, walk back, and sit down on the chair again, at which point the timer will be stopped)[12]
  2. Falls: We will ask the patient if they have experienced a fall (s) in the preceding year
  3. Nutrition: We will use the height and weight to calculate the body mass index (BMI – weight in kilograms divided by the height in meters squared) and we will ask whether the patient has experienced any unintentional weight loss. In the retrospective portion of the study, we realized that several patients had a low BMI without unintentional weight loss, perhaps reflecting that some Indians may be constitutionally thinner than global standards. Several other patients had never weighed themselves and were unable to quantify the degree of weight loss. We therefore started administering the MNA as well, for which we measured the mid-arm and the mid-thigh circumference with a measuring tape[13]
  4. Psychological: We will screen for the presence of depression with the GDS-Short Form[14] and for the presence of anxiety with the GAD-7[15]
  5. Comorbidities: These will be assessed using the Charlson Comorbidity Index[16] and/or the Cumulative Illness Rating Scale for Geriatrics[17]
  6. Cognition: In the retrospective portion of the study, we used the full Mini-Mental State Examination.[18] Although this takes a longer time than the short cognitive screening tools like the Mini-Cog Test[19] and Blessed Orientation-Memory-Concentration Test,[20] early on, we found that these are not culturally appropriate in the Indian setting. Many of the patients do not know how to read, or how to draw time on a clock, and many patients do not know the exact time, or the months of the year as per the Gregorian calendar
  7. Social: We will record the living situation of the patient, how many persons he/she is living with, how many caregivers are available, and who exactly the caregivers are. We will evaluate the social support with the use of OARS-MSS[21] or the RAND Medical Outcomes Study Social Support Survey Resources (MOS-SSS)[22]
  8. Screening tools: We will score the patients using the G8 questionnaire,[23] VES-13[24] and the Triage Risk Screening Tool (TRST),[25] in an attempt to assess whether these screening tools can reliably predict a deficit in the CGA in our Indian patients.


Scoring of the geriatric scales

We will use the standard scoring systems described with the tools [Table 1].

Chemotherapy risk assessment

We will use either the Chemotherapy Risk Assessment Scale for High-Age Patients tool[26] or the Cancer and Aging Research Group (CARG) online toxicity tool[27],[28] to assess the chemotherapy toxicity risk for the patients. CARG Score risk groups are as per the derivation study: low risk (score 0–5), intermediate risk (score 6–9), and high risk (score ≥10).

Determination of non-cancer life expectancy

We will use the ePrognosis website to determine the Lee and the Schonberg Index for each patient.[29]

Quality of life

From July 2019 onward, we have requested patients to fill out QoL forms (European Organization for Research and Treatment of Cancer QLQ-C30, v. 3.0).[30] The QLQ-C30 questionnaire consists of thirty questions, including five multi-item functioning scales (physical, role, social, emotional, and cognitive functioning), nine symptom scales (pain, fatigue, nausea/vomiting, constipation, sleep, appetite, dyspnea, and financial impact), and two items that measure overall health/QoL. We asked the caregiver accompanying the patient to fill out the Caregiver Burden Scale if they were willing. The Caregiver Burden Scale consists of a 22-item self-administered questionnaire that assesses the experience of the caregiver in terms of caring for the patient. Each question has five possible answers ranging from never (0 points) to nearly always (4 points). Total score ranges from 0 to 88, with a score of 0–20 signifying little or no burden; 21–40 = mild-to-moderate burden; 41–60 = moderate-to-severe burden; 61–88 = severe burden.[31]

Statistical analysis

Sample size

As this is a retrospective analysis, no calculation for sample size has been done. For the analysis, we will include all patients who have been included in the geriatric oncology database.



Statistical analysis

Data are prospectively entered in a Microsoft Excel database. Data will be entered into SPSS v. 20 for the purpose of analysis.

Demographics, clinical details, deficits in the various domains, polypharmacy, and the presence of potentially inappropriate medications will be presented with descriptive statistics, using absolute numbers, simple percentages, median, range, and interquartile range. If even a single test was used to assess a particular domain, then that domain will be considered to have been tested in that patient. To calculate the proportion of patients with a deficit in a particular domain, the denominator will be all the patients in whom that domain was tested.

To evaluate the screening tests-G8, VES and TRST, we will calculate the sensitivity, specificity, positive predictive value, negative predictive value, likelihood ratio of a positive and negative test, overall accuracy, and area under the receiver operating characteristic curve (ROC AUC) for each screening tool.

For toxicity assessment, the details of toxicity of chemotherapy will be captured from the electronic medical record and the patient's clinical file and will be scored according to the common toxicity criteria for adverse events (CTCAE), v. 5. Simple percentages will be used to describe toxicity. Association between the CARG chemotherapy risk score and the development of severe toxicity will be tested using Chi-tests of association. Univariate and multivariate logistic regression will be used to explore potential associations between toxicity and covariates, with the CARG Score treated as a continuous variable.

For evaluation of PFS (calculated as the date of diagnosis to date of disease progression either objectively on scan or date of symptomatic deterioration in the absence of objective evidence of PD or date of death from any cause) and OS (calculated as the date of diagnosis to date of death from any cause), survival analysis will be done by Kaplan-Meier method. To evaluate the factors that affect survival and toxicity, log-rank test and Cox proportional hazard model will be used.

The mean scores and standard deviations of health-related QoL scores will be calculated according to the EORTC QLQ scoring manual and using percentages, means, standard deviations, t-test, and Chi-squared test.

Ethical considerations

This is a standard assessment of patients who have undergone routine CGA. Once IEC approval has been obtained, we will include patients after obtaining written informed consent. Since the geriatric evaluation is part of routine care, there are no ethical considerations. At the time of analysis and publication, the patient data will be anonymized, and no form of patient identity will be revealed.


  References Top


  1. Available from: https://www.nih.gov/news-events/news-releases/worlds-older-population-grows-dramatically. [Last accessed on 2019 Nov 28].
  2. Available from: https://www.indiatoday.in/magazine/nation/story/20180507-branded-corporate-elderly-care-old-age-homes-1221657-2018-04-26. [Last accessed on 2019 Nov 28].
  3. Available from: https://economictimes.indiatimes.com/news/politics-and-nation/demographic-time-bomb-young-india-ageing-much-faster-than-expected/articleshow/65382889.cms?from=mdr. [Last accessed on 2019 Nov 28].
  4. Available from: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2019/cancer-facts-and-figures-2019.pdf. [Last accessed on 2019 Nov 28].
  5. Yeole BB, Kurkure AP, Koyande SS. Geriatric cancers in India: An epidemiological and demographic overview. Asian Pac J Cancer Prev 2008;9:271-4.
  6. Mohile SG, Dale W, Somerfield MR, Schonberg MA, Boyd CM, Burhenn PS, et al. Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology. J Clin Oncol 2018;36:2326-47.
  7. Wildiers H, Heeren P, Puts M, Topinkova E, Janssen-Heijnen ML, Extermann M, et al. International Society of Geriatric Oncology consensus on geriatric assessment in older patients with cancer. J Clin Oncol 2014;32:2595-603.
  8. By the 2019 American Geriatrics Society Beers Criteria® Update Expert Panel. American geriatrics society 2019 updated AGS Beers Criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc 2019;67:674-94.
  9. Avlund K, Holstein BE. Functional ability among elderly people in three service settings: The discriminatory power of a new functional ability scale. Eur J Epidemiol 1998;14:783-90.
  10. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The index of ADL: A standardized measure of biological and psychosocial function. JAMA 1963;185:914-9.
  11. Lawton MP, Brody EM. Assessment of older people: Self-monitoring and instrumental activities of daily living. Gerontologist 1969;9:179-86.
  12. Shumway-Cook A, Brauer S, Woollacott M. Predicting the probability for falls in community-dwelling older adults using the timed up & go test. Phys Ther 2000;80:896-903.
  13. Vellas B, Guigoz Y, Garry PJ, Nourhashemi F, Bennahum D, Lauque S, et al. The Mini Nutritional Assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition 1999;15:116-22.
  14. Almeida OP, Almeida SA. Short versions of the geriatric depression scale: A study of their validity for the diagnosis of a major depressive episode according to ICD-10 and DSM-IV. Int J Geriatr Psychiatry 1999;14:858-65.
  15. Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: The GAD-7. Arch Intern Med 2006;166:1092-7.
  16. 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.
  17. Wedding U, Roehrig B, Klippstein A, Steiner P, Schaeffer T, Pientka L, et al. Comorbidity in patients with cancer: Prevalence and severity measured by cumulative illness rating scale. Crit Rev Oncol Hematol 2007;61:269-76.
  18. Pangman VC, Sloan J, Guse L. An examination of psychometric properties of the mini-mental state examination and the standardized mini-mental state examination: Implications for clinical practice. Appl Nurs Res 2000;13:209-13.
  19. 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.
  20. Fillenbaum GG, Heyman A, Wilkinson WE, Haynes CS. Comparison of two screening tests in Alzheimer's disease. The correlation and reliability of the Mini-Mental State Examination and the modified Blessed test. Arch Neurol 1987;44:924-7.
  21. Burholt V, Windle G, Ferring D, Balducci C, Fagerström C, Thissen F, et al. Reliability and validity of the Older Americans Resources and Services (OARS) social resources scale in six European countries. J Gerontol B Psychol Sci Soc Sci 2007;62:S371-9.
  22. Kornblith AB, Herndon JE 2nd, Zuckerman E, Viscoli CM, Horwitz RI, Cooper MR, et al. Social support as a buffer to the psychological impact of stressful life events in women with breast cancer. Cancer 2001;91:443-54.
  23. Agemi Y, Shimokawa T, Sasaki J, Miyazaki K, Misumi Y, Sato A, et al. Prospective evaluation of the G8 screening tool for prognostication of survival in elderly patients with lung cancer: A single-institution study. PLoS One 2019;14:e0210499.
  24. Joshi A, Tandon N, Patil VM, Noronha V, Gupta S, Bhattacharjee A, et al. Agreement analysis between three different short geriatric screening scales in patients undergoing chemotherapy for solid tumors. J Cancer Res Ther 2017;13:1023-6.
  25. Lee JS, Schwindt G, Langevin M, Moghabghab R, Alibhai SM, Kiss A, et al. Validation of the triage risk stratification tool to identify older persons at risk for hospital admission and returning to the emergency department. J Am Geriatr Soc 2008;56:2112-7.
  26. Extermann M, Boler I, Reich RR, Lyman GH, Brown RH, DeFelice J, et al. Predicting the risk of chemotherapy toxicity in older patients: The Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) score. Cancer 2012;118:3377-86.
  27. Hurria A, Togawa K, Mohile SG, Owusu C, Klepin HD, Gross CP, et al. Predicting chemotherapy toxicity in older adults with cancer: A prospective multicenter study. J Clin Oncol 2011;29:3457-65.
  28. Available from: http://www.mycarg.org/Chemo_Toxicity_Calculator. [Last accessed on 2019 Nov 02]
  29. Available from: https://eprognosis.ucsf.edu/leeschonberg.php. [Last accessed on 2019 Nov 02].
  30. Available from: https://www.eortc.org/app/uploads/sites/2/2018/08/Specimen-QLQ-C30-English.pdf. [Last accessed on 2019 Nov 02].
  31. Zarit SH, Reever KE, Bach-Peterson J. Relatives of the impaired elderly: Correlates of feelings of burden. Gerontologist 1980;20:649-55.




 
  References Top

1.
White MC, Holman DM, Boehm JE, Peipins LA, Grossman M, Henley SJ. Age and cancer risk: A potentially modifiable relationship. Am J Prev Med 2014;46:S7-15.  Back to cited text no. 1
    
2.
Korc-Grodzicki B, Sun SW, Zhou Q, Iasonos A, Lu B, Root JC, et al. Geriatric assessment as a predictor of delirium and other outcomes in elderly patients with cancer. Ann Surg 2015;261:1085-90.  Back to cited text no. 2
    
3.
Kristjansson SR, Nesbakken A, Jordhøy MS, Skovlund E, Audisio RA, Johannessen HO, et al. Comprehensive geriatric assessment can predict complications in elderly patients after elective surgery for colorectal cancer: A prospective observational cohort study. Crit Rev Oncol Hematol 2010;76:208-17.  Back to cited text no. 3
    
4.
Soubeyran P, Fonck M, Blanc-Bisson C, Blanc JF, Ceccaldi J, Mertens C, et al. Predictors of early death risk in older patients treated with first-line chemotherapy for cancer. J Clin Oncol 2012;30:1829-34.  Back to cited text no. 4
    
5.
Extermann M, Aapro M, Bernabei R, Cohen HJ, Droz JP, Lichtman S, et al. Use of comprehensive geriatric assessment in older cancer patients: Recommendations from the task force on CGA of the International Society of Geriatric Oncology (SIOG). Crit Rev Oncol Hematol 2005;55:241-52.  Back to cited text no. 5
    
6.
Mohile SG, Dale W, Somerfield MR, Schonberg MA, Boyd CM, Burhenn PS, et al. Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology. J Clin Oncol 2018;36:2326-47.  Back to cited text no. 6
    
7.
Fallahzadeh R, Rokni SA, Ghasemzadeh H, Soto-Perez-de-Celis E, Shahrokni A. Digital Health for Geriatric Oncology. JCO Clin Cancer Inform 2018;2:1-12.  Back to cited text no. 7
    
8.
Leist AK. Social media use of older adults: A mini-review. Gerontology 2013;59:378-84.  Back to cited text no. 8
    
9.
Ollevier A, Aguiar G, Palomino M, Simpelaere IS. How can technology support ageing in place in healthy older adults? A systematic review. Public Health Rev 2020;41:26.  Back to cited text no. 9
    
10.
Levine DM, Lipsitz SR, Linder JA. Trends in seniors' use of digital health technology in the United States, 2011-2014. JAMA 2016;316:538-40.  Back to cited text no. 10
    
11.
Noronha V, Ramaswamy A, Dhekle R, Talreja V, Gota V, Gawit K, et al. Initial experience of a geriatric oncology clinic in a tertiary cancer center in India. Cancer Res Stat Treat 2020;3:208.  Back to cited text no. 11
  [Full text]  
12.
Katz S. Assessing self-maintenance: Activities of daily living, mobility, and instrumental activities of daily living. J Am Geriatr Soc 1983;31:721-7.  Back to cited text no. 12
    
13.
Tombaugh TN, McIntyre NJ. The mini-mental state examination: A comprehensive review. J Am Geriatr Soc 1992;40:922-35.  Back to cited text no. 13
    
14.
Tsolaki M, Iakovidou V, Navrozidou H, Aminta M, Pantazi T, Kazis A. Hindi Mental State Examination (HMSE) as a screening test for illiterate demented patients. Int J Geriatr Psychiatry 2000;15:662-4.  Back to cited text no. 14
    
15.
Parikh PM, Chaitanya K, Boppana M, Kumar MS, Shankar K. Geriatric oncology landscape in India – Current scenario and future projections. Cancer Res Stat Treat 2020;3:296.  Back to cited text no. 15
  [Full text]  
16.
Ester M, McNeely ML, McDonough MH, Culos-Reed SN. A survey of technology literacy and use in cancer survivors from the Alberta Cancer Exercise program. Digit Health. 2021;7:20552076211033426. doi: 10.1177/20552076211033426.   Back to cited text no. 16
    
17.
Low ST, Sakhardande PG, Lai YF, Long AD, Kaur-Gill S. Attitudes and perceptions toward healthcare technology adoption among older adults in Singapore: A qualitative study. Front Public Health 2021;9:588590.  Back to cited text no. 17
    
18.
Fischer SH, David D, Crotty BH, Dierks M, Safran C. Acceptance and use of health information technology by community-dwelling elders. Int J Med Inform 2014;83:624-35.  Back to cited text no. 18
    
19.
Gell NM, Rosenberg DE, Demiris G, LaCroix AZ, Patel KV. Patterns of technology use among older adults with and without disabilities. Gerontologist 2015;55:412-21.  Back to cited text no. 19
    
20.
Roupa Z, Nikas M, Gerasimou E, Zafeiri V, Giasyrani L, Kazitori E, et al. The use of technology by the elderly. Health Sci J 2010;4: 118-26.   Back to cited text no. 20
    
21.
Kim J, Lee HY, Christensen MC, Merighi JR. Technology access and use, and their associations with social engagement among older adults: Do women and men differ? J Gerontol B Psychol Sci Soc Sci 2017;72:836-45.  Back to cited text no. 21
    
22.
Smith A. Older Adults and Technology Use. Pew Research Center: Internet, Science & Tech; 2014. Available from: https://www.pewresearch.org/internet/2014/04/03/older-adults-and-technology-use/. [Last accessed on 2021 Nov 11].  Back to cited text no. 22
    
23.
Moen P, Flood S. Limited engagements? Women's and men's work/volunteer time in the encore life course stage. Soc Probl 2013;60:10.1525/sp.2013.60.2.206.   Back to cited text no. 23
    
24.
Karavidas M, Lim NK, Katsikas SL. The effects of computers on older adult users. Comput Hum Behav 2005;21:697-711.  Back to cited text no. 24
    
25.
Xie B. Older adults, computers, and the Internet: Future directions. Gerontechnology 2003;2:289-305.  Back to cited text no. 25
    
26.
Bhakhri R, Chun R, Coalter J, Jay WM. A survey of smartphone usage in low vision patients. Invest Ophthalmol Vis Sci 2012;53:4421.  Back to cited text no. 26
    
27.
Quittschalle J, Stein J, Luppa M, Pabst A, Löbner M, Koenig HH, et al. Internet use in old age: Results of a German population-representative survey. J Med Internet Res 2020;22:e15543.  Back to cited text no. 27
    
28.
Sun X, Yan W, Zhou H, Wang Z, Zhang X, Huang S, et al. Internet use and need for digital health technology among the elderly: A cross-sectional survey in China. BMC Public Health 2020;20:1386.  Back to cited text no. 28
    
29.
Technology Use among Seniors. Pew Research Center: Internet, Science & Tech; 2017. Available from: https://www.pewresearch.org/internet/2017/05/17/technology-use-among-seniors/. [Last accessed on 2021 Nov 11].  Back to cited text no. 29
    
30.
Choi NG, Dinitto DM. Internet use among older adults: Association with health needs, psychological capital, and social capital. J Med Internet Res 2013;15:e97.  Back to cited text no. 30
    
31.
Ang S, Lim E, Malhotra R. Health-related difficulty in internet use among older adults: Correlates and mediation of its association with quality of life through social support networks. Gerontologist 2021;61:693-702.  Back to cited text no. 31
    
32.
Chopik WJ. The benefits of social technology use among older adults are mediated by reduced loneliness. Cyberpsychol Behav Soc Netw 2016;19:551-6.  Back to cited text no. 32
    
33.
Silver L, Smith A, Johnson C, Jiang J, Monica A, Rainie L. Use of smartphones and social media is common across most emerging economies. Pew Res Center 2019;1-92. Available from: https://www.pewresearch.org/internet/2019/03/07/use-of-smartphones-and-social-media-is-common-across-most-emerging-economies/. [Last accessed on 2021 Nov 11].  Back to cited text no. 33
    
34.
Lauriks S, Reinersmann A, Van der Roest HG, Meiland FJ, Davies RJ, Moelaert F, et al. Review of ICT-based services for identified unmet needs in people with dementia. Ageing Res Rev 2007;6:223-46.  Back to cited text no. 34
    
35.
Topo P. Technology studies to meet the needs of people with dementia and their caregivers: A literature review. J Appl Gerontol 2009;28:5-37.  Back to cited text no. 35
    
36.
Lundberg S. The results from a two-year case study of an information and communication technology support system for family caregivers. Disabil Rehabil Assist Technol 2014;9:353-8.  Back to cited text no. 36
    
37.
Magnusson L, Hanson E, Borg M. A literature review study of Information and Communication Technology as a support for frail older people living at home and their family carers. Technol Disabil 2004;16:223-35.  Back to cited text no. 37
    
38.
Cassie KM, Sanders S. Familial caregivers of older adults. J Gerontol Soc Work 2008;50 Suppl 1:293-320.  Back to cited text no. 38
    
39.
Ugalde A, Gaskin CJ, Rankin NM, Schofield P, Boltong A, Aranda S, et al. A systematic review of cancer caregiver interventions: Appraising the potential for implementation of evidence into practice. Psychooncology 2019;28:687-701.  Back to cited text no. 39
    
40.
Lapid MI, Atherton PJ, Clark MM, Kung S, Sloan JA, Rummans TA. Cancer caregiver: Perceived benefits of technology. Telemed J E Health 2015;21:893-902.  Back to cited text no. 40
    
41.
Richards R, Kinnersley P, Brain K, McCutchan G, Staffurth J, Wood F. Use of mobile devices to help cancer patients meet their information needs in non-inpatient settings: Systematic review. JMIR Mhealth Uhealth 2018;6:e10026.  Back to cited text no. 41
    


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