High prevalence of malnutrition in geriatric patients with solid organ cancer: An institutional study

doi:10.21203/rs.3.rs-4834626/v1

Download PDF

Research Article

High prevalence of malnutrition in geriatric patients with solid organ cancer: An institutional study

https://doi.org/10.21203/rs.3.rs-4834626/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Objectives

The demographic transition towards aging heralds an increase in the number of geriatric patients with cancer in India. Comprehensive geriatric assessment (CGA) is a sine qua non for the treatment planning and shared decision-making in this group of patients. We aimed to study the prevalence of malnutrition and the associated risk factors in geriatric patients with solid organ cancer (SOC).

Methods

In this observational study, geriatric patients with cancer and naïve to systemic anti-cancer therapy underwent CGA. was We performed a Mini nutritional assessment (MNA) to diagnose malnutrition status. Data analysis was done using descriptive statistics, Pearson Chi-Square, Spearman correlation, and multivariable regression analysis to assess the factors associated with malnutrition.

Results

One hundred and forty-two patients were included in the analysis. The median age was 67 (range 60–88) years, with a male preponderance (73.2%) and a stage IV (75.4%) disease. The majority of the patients, 91.6% (n = 130), had abnormal MNA scores during CGA. Nearly 1/3rd of the subjects, 35.2% (n = 50), were underweight (Body-mass index < 18.5 Kg/m2). Poor performance status was seen in 30.3% of the subjects. Poor appetite (79.6%) was the most common risk factor, followed by addictions (73.1%), chronic constipation (35.9%), and polypharmacy (21.8%). Cognitive impairment and depression were seen in 35.2% and 57.1% of the subjects, respectively. The study found a significant correlation of MNA with age (p = 0.048), depression (P < 0.001), PS (P < 0.001), functional decline (P < 0.001), and cognition (P < 0.001).

Conclusions

There exists a widespread prevalence of malnutrition and amenable risk factors in geriatric cancer patients. Nutritional assessment is essential, and interventions should be implemented to improve clinical outcomes.

Malnutrition

Geriatric Patients

Mini Nutritional Assessment

Comprehensive Geriatric Assessment

Functional Decline

Nutritional Status

The proportion of people aged 60 years and above is growing rapidly worldwide and is expected to reach 2.1 billion by 2050 [1]. At the same time, life expectancy in India is improving, currently standing at 70.4 years, with almost 10.7% of the population aged 60 years and above [2, 3]. India is staring at a precipitous demographic transition with an estimated increase in the geriatric population (up to 324 million) over the next two and a half decades, as currently, two-thirds of the population is under 35 years of age [4]. Since aging has been recognized as one of the most significant risk factors for cancer, the perspectives of geriatric oncology in India and other low- and middle-income countries seem challenging. Among various concerns with geriatric patients with cancer, malnutrition is common and has become a critical public health issue that often goes unrecognized. Malnutrition is significantly linked with poor oncological outcomes, morbidities, disabilities, reduced overall quality of life, and increased all-cause mortality, making it a serious concern that needs to be addressed [5, 6, 7].

The geriatric population is prone to malnutrition due to various risk factors, which get accelerated in the presence of cancer. The significant factors associated with malnutrition in geriatric patients with cancer are frailty, polypharmacy, impaired cognition, dementia, and poor appetite, apart from other factors like living alone, financial constraints, addictions, comorbidities, low social support, and neglect [8, 9]. The American Society of Clinical Oncology (ASCO) strongly recommends a comprehensive geriatric assessment (CGA) in these patients to identify vulnerabilities that are not usually assessed through oncology assessment. Nutritional status assessment should be part of CGA prior to planning systemic therapy for geriatric patients with cancer and should be adopted as early as possible. However, this seems to be lacking in practice [10, 11].

A post-hoc analysis of NutriCancer 2012, a French observational multicentre cross-sectional study of malnutrition in elderly patients with cancer, found elderly patients to be more frequently malnourished than younger patients ( 44.9% vs. 36.7%, p = 0.0006) [12]. Another cross-sectional study by Zhang X et al. found malnutrition to be prevalent in 41.9% of the geriatric patients diagnosed with cancer. These patients were more likely to have depression and frailty as compared to those without malnutrition. Based on recent research conducted by Vanita Noronha et al. among Indian elderly patients with cancer, 65% of patients had an abnormal nutritional status, emphasizing the gravity of the problem [13, 14].

The conception of geriatric oncology clinics and the CGA is still in the primitive stage in India. Only a few cancer centers in our country offer dedicated geriatric oncology services. Moreover, geographical and socio-economic-cultural differences and the paucity of data from our country

prompted us to conduct the current study. The primary and secondary objectives were to identify the risk factors associated with malnutrition and the correlation of malnutrition with gender, performance status (PS), stage of the disease, depression, and cognitive decline, respectively. This study depicts an honest attempt to find out various factors associated with malnutrition in geriatric patients with solid organ cancer (SOC). It emphasizes the need for CGA in every geriatric oncology patient. Timely identifying these factors and other vulnerabilities can lead to early intervention to prevent poor outcomes from chemotherapy and the disease itself.

This cross-sectional, observational study was conducted at All India Institute of Medical Sciences, Rishikesh, India. A dedicated geriatric oncology clinic was started once weekly in February 2021. We enrolled patients from geriatric oncology outpatient and in-patient services from April 2021 to December 2022. The institutional research board reviewed the study protocol, followed by the institutional ethics committee approval (AIIMS/IEC/22/129). Guidelines laid by the Indian Council for Medical Research, good clinical practice guidelines, and those mentioned in the Declaration of Helsinki were followed stringently.

We included patients aged 60 years and above diagnosed with SOC and naïve for definitive anti-cancer treatment. Patients intended for hospice care or those using appetite stimulants or alternative systems of medicine were excluded from the study.

The study methodology was explained to participants, and informed written consent was obtained. Demographic information, clinical history and examination findings, and laboratory and imaging findings were noted. Screening for the geriatric assessment by the G8 tool and CGA was done by trained medical oncology residents as per the American Society of Clinical Oncology (ASCO) guidelines [15, 16]. The various domains assessed included function by Eastern Cooperative Oncology Group-PS (ECOG-PS), activities of daily living (ADL) by Katz tool, instrumental Activities of Daily Living (IADL) by Lawton and Brody Scale, timed-Up-and-Go Test (TUG), cognition by Hindi Mental State Examination (HMSE), psychological assessment by Geriatric Depression Scale (GDS), nutrition by body mass index (BMI) and mini nutritional assessment (MNA), and comorbidities assessment by cumulative illness rating scale for geriatrics (CIRS-G) [17, 18, 19, 20, 21, 22, 23]. In addition, an assessment of social support in the form of availability of caregivers, elderly abuse, financial support, and polypharmacy was done. Chemotherapy risk assessment was done using the Cancer and Aging Research Group (CARG) toxicity tool [24].

The sample size was determined using the modified Cochran Formula for sample size calculation in smaller populations and considering the proportion of geriatric oncology patients with abnormal MNA as 75% based on a previous study [14]. The derived sample size was 163. The accrual was slower than expected due to the COVID-19 pandemic and the resultant lockdown. One-hundred forty-two patients were considered for the final analysis. For statistical analysis, descriptive statistics were calculated, including mean, median, standard deviation, range for continuous variables, and relative frequencies for categorical variables. Pearson's Chi-Square Test, Fisher's Exact Test, Kruskal Wallis Test, Wilcoxon-Mann-Whitney U Test, and Spearman correlation were used to assess the association between discrete variables and malnutrition status.

The demographic and clinical details are mentioned in Table 1. Two hundred and twenty patients were screened during the study period, and 142 patients were considered for the final study participation. The median age of the participants was 67 years ( IQR 62.00–71.00), with the majority of the participants (67.6%) between 60 and 69 years of age and males (73.2%). The most common malignancies identified in descending order were lung, ovarian, colorectal, urinary bladder, esophageal, prostatic carcinoma, and others, with 75.4% of the patients being diagnosed with metastatic disease. More than 55% of the patients were found to have one or more comorbid illnesses, while almost 75% of the patients were addicted to either smoking, smokeless tobacco, alcohol, or a combination.

Table 1

**Demographic and clinical details**
Basic Details	Median (IQR) OR n (%)
Age (Years)	67.00 (62.00–71.00)
Age distribution
60–69 Years	96 (67.6%)
70–79 Years	41 (28.9%)
80–89 Years	5 (3.5%)
Gender
Male	104 (73.2%)
Female	38 (26.8%)
BMI (kg/m²)	20.30 (17.42–22.28)
<18.5 Kg/m²	50 (35.2%)
18.5–24.9 Kg/m²	76 (53.3%)
25.0-29.9 Kg/m²	11 (7.7%)
30.0-34.9 Kg/m²	5 (3.5%)
Addiction
None	36 (25.4%)
Smoking only	65 (45.8%)
Alcohol only	3 (2.1%)
Smokeless Tobacco only	5 (3.5%)
Smoking + Alcohol	28 (19.7%)
Smoking + Smokeless Tobacco	3 (2.1%)
Smoking + Smokeless Tobacco + Alcohol	2 (1.4%)
Comorbidities
Hypertension	34 (23.9%)
Diabetes Mellitus	23 (16.2%)
COPD	9 (6.3%)
Coronary Artery Disease	8 (5.6%)
Hypothyroidism	2 (1.4%)
Osteoarthritis	2 (1.4%)
Tuberculosis	1 (0.7%)
Site of the cancer
Breast	4 (2.8%)
Carcinoma of Unknown Primary	3 (2.1%)
Gastro-intestinal	30 (21.1%)
Genito-urinary	21 (14.7%)
Gynecological	16 (11.3%)
Head & Neck	4 (2.8%)
Lung	54 (38.0%)
Pancreatico-biliary	9 (6.3%)
Skin	1 (0.7%)
Stage
Stage II	6 (4.2%)
Stage III	29 (20.4%)
Stage IV	107 (75.4%)

BMI : Body-Mass Index; COPD: Chronic Obstructive Pulmonary Disease

The median G8 tool score was 9 (IQR 6–11), with 96.4% of the patients depicting a geriatric risk profile. The functional impairment assessed by ADL and IADL were found to be abnormal in 39.4% and 20.4% of the patients, respectively. As per the TUG test, functional decline and the probability of falls were detected in 55.6% of the patients. The majority of the participants (66.2%) had a poor ECOG-PS of 2 and above. The median HMSE score was 25 (IQR (22–28), with 35.2% of the patients with impaired results. GDS was found to be abnormal in 57.1% of the patients. The median MNA score was 8 (IQR 5–10), with the majority of the patients ( 91.6%) having an abnormal result (Table 2).

Table 2

Outcomes of various CGA domains
CGA domains	Outcome (n = 142)
Screening - G8	137 abnormal
ADL (Katz tool)	56 abnormal
ECOG-PS stratification
0	5 (3.5%)
1	43 (30.3%)
2	51 (35.9%)
3	36 (25.4%)
4	7 (4.9%)
IADL (Lawton and Brody Scale)	29 abnormal
HMSE	25.00 (22.00–28.00)
Normal Cognition	92 (64.8%)
Mild Cognitive Impairment	27 (19.0%)
Moderate Cognitive Impairment	23 (16.2%)
Severe Cognitive Impairment	0 (0.0%)
GDS	5.00 (3.00–8.00)
GDS Category
Normal	61 (43.0%)
Mild Depression	50 (35.2%)
Moderate Depression	19 (13.4%)
Severe Depression	12 (8.5%)
MNA	8.00 (5.00–10.00)
MNA Category
Malnourished	69 (48.6%)
At Risk	61 (43.0%)
Normal	12 (8.5%)
TUG Test
≤11 Seconds	63 (44.4%)
>11 Seconds	79 (55.6%)
ADL: Activities of Daily Living; CGA: Comprehensive Geriatric assessment; ECOG-PS: Eastern Cooperative Oncology Group-Performance Status; GDS: Geriatric Depression Scale; HMSE: Higher Mental State Examination; IADL: Instrumental Activities of Daily Living; MNA: Mini Nutritional Assessment; TUG: Timed Up and Go Test

The most commonly identified risk factors for malnutrition were poor appetite, addictions, chronic constipation, and cognitive decline in 79.5%, 74.6%, 35.9%, and 35.2% of the patients, respectively, followed by polypharmacy, dysphagia/odynophagia and chronic diarrhea (Table 3).

Table 3

Risk factors for malnutrition
Factor	Result ( n = 142)
Poor appetite	113 (79.5%)
Addiction	106(74.6%)
Chronic constipation	51(35.9%)
Cognitive decline	50(35.2%)
Polypharmacy	31(21.8%)
Dysphagia/odynophagia	14(9.8%)
Chronic diarrhoea	13(9.1%)

Correlation of MNA scores with other domains/risk factors

The univariate analysis revealed a weak negative correlation between age (years) and MNA, which was statistically significant (rho = -0.17, P = 0.048). For every 1 unit increase in age (years), the MNA reduced by 0.07 units. There was a moderate negative correlation between depression and MNA, which was statistically significant (rho = -0.43, P = < 0.001). For every 1 unit increase in GDS, the MNA is reduced by 0.37 units. The Spearman correlation revealed a moderate negative correlation between the PS and MNA, which was statistically significant (rho = -0.59, P = < 0.001). For every 1 unit increase in PS (ECOG), the MNA decreased by 2.01 units. Conversely, for every 1 unit increase in the MNA, the PS decreased by 0.19 units. Similarly, functional impairment, as assessed by ADL/IADL, was found to have a significant correlation with MNA (P < 0.001). Probability of falls detected by the TUG test was also significant (P < 0.001).

A statistically significant, moderate positive correlation between HMSE and MNA was detected; for every 1 unit increase in the MNA, the HMSE increased by 0.54 units (rho = 0.39, P = < 0.001). This study did not show the correlation of MNA with gender, polypharmacy, and stage of the disease (Table 4). On multivariate analysis, depression, ECOG-PS and TUG test were the only factors significantly associated with the MNA (Table 5).

Table 4

Correlation of MNA with other domains/risk factors
Parameters	Mini-Nutritional Assessment	P -value
Age (Years)***	Correlation Coefficient (rho) = -0.17	0.048¹
Gender		0.158³
Male	7.18 ± 3.16
Female	7.97 ± 2.79
BMI (kg/m²)***	Correlation Coefficient (rho) = 0.58	< 0.001¹
BMI***		< 0.001²
<18.5 Kg/m²	5.46 ± 2.50
18.5–22.9 Kg/m²	7.70 ± 2.70
23.0-24.9 Kg/m²	9.88 ± 1.75
25.0-29.9 Kg/m²	10.09 ± 2.26
30.0-34.9 Kg/m²	9.20 ± 5.40
Any Comorbidity		0.483³
Yes	7.62 ± 2.97
No	7.23 ± 3.09
Any Addiction		0.067³
Yes	7.04 ± 3.19
No	8.06 ± 2.86
Stage		0.372²
Stage I	-
Stage II	9.00 ± 3.79
Stage III	6.90 ± 2.60
Stage IV	7.44 ± 3.15
Dysphagia/Odynophagia		0.564³
Yes	7.07 ± 2.34
No	7.43 ± 3.16
Chronic Diarrhoea		0.738³
Yes	7.62 ± 2.60
No	7.37 ± 3.13
Chronic Constipation		0.616³
Yes	7.25 ± 2.99
No	7.47 ± 3.14
Poor appetite ***		< 0.001³
Yes	6.89 ± 3.00
No	9.34 ± 2.62
Polypharmacy		0.915³
Yes	7.42 ± 3.03
No	7.39 ± 3.11
ADL***	Correlation Coefficient (rho) = 0.48	< 0.001¹
ECOG-PS***	Correlation Coefficient (rho) = -0.59	< 0.001¹
IADL (Lawton and Brody Scale) - Male***	Correlation Coefficient (rho) = 0.58	< 0.001¹
IADL (Lawton and Brody Scale) - Female***	Correlation Coefficient (rho) = 0.53	0.001¹
HMSE***	Correlation Coefficient (rho) = 0.39	< 0.001¹
TUG Test***		< 0.001³
≤11 Seconds	9.44 ± 2.33
>11 Seconds	5.76 ± 2.59
HMSE Category***		0.001²
Normal Cognition	8.02 ± 2.92
Mild Cognitive Impairment	7.04 ± 2.95
Moderate Cognitive Impairment	5.30 ± 2.96
Severe Cognitive Impairment	-
GDS***	Correlation Coefficient (rho) = -0.43	< 0.001¹
GDS Category***		0.001²
Normal	8.54 ± 2.84
Mild Depression	6.90 ± 2.88
Moderate Depression	6.32 ± 3.13
Severe Depression	5.33 ± 3.08
***Significant at P < 0.05, 1: Spearman Correlation, 2: Kruskal Wallis Test, 3: Wilcoxon-Mann-Whitney U Test BMI: Body-Mass Index; ADL: Activities of Daily Living; ECOG-PS: Eastern Cooperative Oncology Group-Performance Status; GDS: Geriatric Depression Scale; HMSE: Higher Mental State Examination; IADL: Instrumental Activities of Daily Living; TUG: Timed Up and Go

Table 5

*Multivariable regression analysis of the factors associated with malnutrition*
Dependent: Mini-Nutritional Assessment		unit	value	Coefficient (univariable)	Coefficient (multivariable)
GDS	[0.0,15.0]	Mean (sd)	7.4 (3.1)	-0.37 (-0.50 to -0.24, P < 0.001)	-0.15 (-0.26 to -0.04, P = 0.009)
HMSE	[11.0,30.0]	Mean (sd)	7.4 (3.1)	0.26 (0.16 to 0.37, P < 0.001)	0.08 (-0.01 to 0.17, P = 0.080)
ECOG-PS	0	Mean (sd)	12.6 (1.7)	-	-
	1	Mean (sd)	9.3 (2.2)	-3.30 (-5.56 to -1.04, P = 0.005)	-2.05 (-4.10 to 0.00, P = 0.050)
	2	Mean (sd)	7.0 (2.6)	-5.60 (-7.84 to -3.36, P < 0.001)	-3.26 (-5.38 to -1.13, P = 0.003)
	3	Mean (sd)	5.9 (2.5)	-6.74 (-9.02 to -4.46, P < 0.001)	-2.69 (-5.09 to -0.29, P = 0.029)
	4	Mean (sd)	2.7 (2.4)	-9.89 (-12.68 to -7.09, P < 0.001)	-4.55 (-7.76 to -1.34, P = 0.006)
ADL	[0.0,6.0]	Mean (sd)	7.4 (3.1)	0.96 (0.69 to 1.23, P < 0.001)	0.34 (-0.01 to 0.70, P = 0.057)
TUG Test	≤ 11 Seconds	Mean (sd)	9.4 (2.3)	-	-
	> 11 Seconds	Mean (sd)	5.8 (2.6)	-3.68 (-4.51 to -2.86, P < 0.001)	-1.94 (-2.87 to -1.02, P < 0.001)
ADL: Activities of Daily Living; ECOG-PS: Eastern Cooperative Oncology Group-Performance Status; GDS: Geriatric Depression Scale; HMSE: Higher Mental State Examination; TUG: Timed Up and Go Test

The present study enables us to identify the prevalence of malnutrition in geriatric patients with cancer from a lower middle-income country with an emphasis on identifying the risk factors and the association between nutritional status and other components of CGA. Poor nutritional status negatively affects the treatment decision with the resultant negative impact on cancer outcomes. Moreover, a critical link between increased all-cause mortality and malnutrition in geriatric oncology patients has already been established. Thus, early identification of associated factors, prevention, and management become the sine qua non [5].

Close to 92% of our patients exhibited abnormal MNA ( 48.6% malnourished, 43% at risk of malnutrition) with a median MNA score of 8.00 (IQR 5.00–10.00), indicating a high prevalence of patients with impaired nutritional status. MNA has been used widely for the assessment of malnutrition in geriatric patients with cancer. In a study of the prognostic value of geriatric assessment in older patients with advanced breast cancer on chemotherapy by Aaldriks AA et al., the MNA indicated that 42% of the patients were either at risk of malnutrition or malnourished [25]. This study included only the patients with breast cancer and had a small sample size. Another study reported by the same authors in the elderly, advanced-stage colorectal cancer patients revealed the prevalence of MNA as 27% [26]. The authors concluded that malnutrition was associated with an increased mortality risk in elderly patients diagnosed with advanced-stage cancer. A prospective study from the ELPACA Study Group done in 993 elderly patients with solid and hematological cancers revealed that 54.4% of the patients had malnutrition at the time of diagnosis [27]. However, a similar Indian study conducted by Noronha V. et al. revealed that 75% of patients had abnormal MNA scores, which is still lower than the results of our study [14]. It is evident from the above studies that the prevalence of malnutrition varies with the type of malignancy, and hence, it is essential to consider MNA as an integral component of CGA in every geriatric patient diagnosed with cancer. An extremely high prevalence of abnormal MNA (malnourished and at risk of malnutrition) in our study can be explained by the fact that our study was carried out in a semi-urban whose catchment area is primarily rural and most of the patients belong to poor socio-economic status. This indicates the necessity for establishing geriatric oncology departments in peripheral institutions so that vulnerabilities, including malnutrition, can be identified and treated early in patients located away from major medical centers. There was no significant difference in MNA scores between males and females, which may be attributed to the marked difference in the proportion of males (73.2%) and females (26.8%) in the study population, as well as the study's single-center design and limited number of patients.

Age-related anorexia is a physiological process that occurs due to a variety of factors, including early and reduced satiety, altered gastro-intestinal motility, impaired cognition, bad dentition, despair, and a lack of social support. Different additional elements, such as an increase in pro-inflammatory cytokines, dysphagia, impaired gastro-intestinal motility, and altered ghrelin release, come into play in an elderly patient with cancer [9, 10]. Together, these variables cause a greater degree of anorexia, which plays a significant role in the development of malnutrition. Our study also reveals that the most prevalent nutrition-related symptom was poor appetite, which was present in 79.6% of study patients. The correlation of MNA with poor appetite also shows a significant correlation (P < 0.001).

Due to the majority of patients having a low level of education and being unable to write, the HMSE was utilized to evaluate the patient's cognitive function. Malnutrition has been associated with cognitive decline resulting from reduced nutrient intake. A systemic review done by Favaro-Moreira NC et al. reported a cognitive decline as a significant risk factor for malnutrition in the older population [8]. A prospective French study conducted by Dos Santos M et al. evaluated cognitive impairment in geriatric patients with cancer planned for chemotherapy. Abnormal cognition and abnormal MNA were detected in 27.7% and 62.9% of the patients, respectively. Further cognitive impairment was observed in 18.7% of the patients during chemotherapy. They concluded that abnormal baseline MNA and MMSE were independent predictive factors of poor outcomes. Thus, timely detection and prompt intervention should be considered prior to systemic therapy (30). Our study's median HMSE score was 25 (IQR 11–30), and 35.2% of patients experienced cognitive decline. A previous Indian study by Noronha V et al. reported impaired cognition in 17.8% of patients (14). Cognition decline was seen in 35.2% of the patients in our study, and a significant correlation between MNA and HMSE scores (P < 0.001) was demonstrated, indicating that poor cognition is a significant risk factor for malnutrition in these patients.

Similar to poor cognition, depression is another factor that can contribute to impaired nutritional status among geriatric patients due to diminished appetite and inadequate food intake [31]. In our study, mild to severe clinical depression, as evaluated by the GDS, was present in 57% of participants, and it exhibited a significant correlation with MNA (p < 0.001). Parrino S et al. evaluated 147 elderly patients with cancer with CGA and found that 26.5% had depression as per GDS. Functional status, nutritional status, cognitive function, and comorbidities were significantly associated (P < 0.05) with depressed mood, but only nutritional status was an independent predictor. They concluded that depression is associated with cognitive, nutritional, and functional decline among geriatric patients with cancer. The significant association with MNA highlights the vicious circle between malnutrition and depression [32]. Severe depression has also been associated with increased mortality in geriatric patients with cancer independent of the major cancer-related prognostic factors [33].

We found that the median ECOG-PS was 2.00 (IQR 1–3), and 66.2% of patients had poor ECOG-PS (2 or more). The correlation of ECOG-PS and MNA scores showed a significant negative correlation. A previous Indian study reported poor ECOG-PS in only 33% of the patients [14]. Borza T et al. reported poor ECOG-PS of 2 or more in 15% of the geriatric patients with cancer. [33]. Abnormalities in the ADL and IADl were seen in 39.4% and 20.4% of the patients in our study, respectively. MNA scores and IADL/ADL were also significantly correlated (P < 0.001). Baseline impairment in functional status or physical function and abnormal nutritional status have been associated with functional decline in previous studies [34, 35].

Three-fourths of the patients in our study had metastatic disease. We did not find any significant association between MNA and stages of malignancy, which may indicate that the majority of patients across all stages were malnourished.

Our study had few limitations. The study was conducted in a single tertiary care academic institution, so our results might not be generalizable to all geriatric cancer patients in different geographic locations. Most of the patients had advanced-stage cancer, so it will be difficult to extrapolate the result in patients suffering from early-stage disease. The data obtained for past medical history may have a recall bias issue.

Our results showed that malnutrition is highly prevalent in Indian geriatric patients with cancer. Poor appetite, addictions, and chronic constipation are the most commonly associated risk factors. Most of these patients have associated cognitive decline, depression, poor PS, and functional decline. It is a well-known fact that a poor baseline nutritional status is associated with poor oncological outcomes specially in head and neck and gastro-intestinal tract cancers. We further suggest studies implementing CGA with dedicated nutritional intervention and early dietary counseling in order to improve clinical outcomes. Incorporating CGA in every geriatric oncology patient is crucial to identifying the presence of malnutrition and other vulnerabilities before they become overt. The unmet need to set up geriatric oncology clinics in most of the peripheral health institutions of India should be addressed as a priority.

Funding statement

No grant was received for this study.

Conflict of interest disclosure
There are no conflicts of interest to disclose.

Ethics approval statement
Approved by the Institutional Ethics Committee letter no : AIIMS/IEC/22/129.

Author Contribution

Conceptualization: DS, and MD.Data collection: DS, AS, MK, NS and UKS. Data analysis: DS, UKS, MK and NS. Drafting the article: DS, AS, and UKS and MD.Critical appraisal and final approval: All authors.

Acknowledgement:

We acknowledge the contribution of geriatric oncology and geriatric medicine clinic for the conduction of this study.

Data availability statement:

Available on reasonable request from the corresponding author.

DECLARATION OF COMPETING INTERESTS

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ageing [Internet]. [cited 2023 May 19]. Available from: https://www.who.int/health-topics/ageing
World Urbanization Prospects - Population Division - United Nations [Internet]. [cited 2023 May 19]. Available from: https://population.un.org/wup/
United Nations, Department of Economic and Social Affairs, Population Division (2022). World Population Prospects 2022, Online Edition.
Ingle GK, Nath A. Geriatric health in India: Concerns and solutions. Indian J Community Med 2008;33:214–18. doi: 10.4103/0970-0218.43225.
Zhang X, Tang T, Pang L, et al. Malnutrition and overall survival in older adults with cancer: A systematic review and meta-analysis. J Geriatr Oncol 2019;10(6):874–83. doi: 10.1016/j.jgo.2019.03.002.
GlobalSurg Collaborative and NIHR Global Health Unit on Global Surgery. Impact of malnutrition on early outcomes after cancer surgery: an international, multicentre, prospective cohort study. Lancet Glob Health 2023;11(3):e341-e349. doi: 10.1016/S2214-109X(22)00550-2.
Bourdel-Marchasson I, Diallo A, Bellera C, et al. One-Year Mortality in Older Patients with Cancer: Development and External Validation of an MNA-Based Prognostic Score. PLoS One 2016;11(2):e0148523. doi: 10.1371/journal.pone.0148523. eCollection 2016.
Fávaro-Moreira NC, Krausch-Hofmann S, Matthys C, et al. Risk Factors for Malnutrition in Older Adults: A Systematic Review of the Literature Based on Longitudinal Data. Adv Nutr 2016;7(3):507–22. doi: 10.3945/an.115.011254.
Damião R, Santos ÁDS, Matijasevich A, Menezes PR. Factors associated with risk of malnutrition in the elderly in south-eastern Brazil. Rev Bras Epidemiol 2017;20(4):598–610. doi: 10.1590/1980-5497201700040004.
Mohile SG, Dale W, Somerfield MR, et al. Practical Assessment and Management of Vulnerabilities in Older Patients Receiving Chemotherapy: ASCO Guideline for Geriatric Oncology. J Clin Oncol 2018;36(22):2326–47. 10.1200/JCO.2018.78.8687.
Sundriyal D, Sehrawat A. Embracing geriatric assessment into the treatment plan: The earlier the better. Cancer Res Stat Treat 2022; 5:717–8. doi: 10.4103/crst.crst_358_22.
Lacau St Guily J, Bouvard É, Raynard B,et al. NutriCancer: A French observational multicentre cross-sectional study of malnutrition in elderly patients with cancer. J Geriatr Oncol 2018;9(1):74–80. doi: 10.1016/j.jgo.2017.08.003.
Zhang X, Pang L, Sharma SV, Li R, Nyitray AG, Edwards BJ. Prevalence and factors associated with malnutrition in older patients with cancer. J Geriatr Oncol 2019;10(5):763–9. doi: 10.1016/j.jgo.2019.01.021.
Noronha V, Ramaswamy A, Dhekle R, et al. Initial experience of a geriatric oncology clinic in a tertiary cancer center in India. Cancer Res Stat Treat 2020;3(2):208–17. doi: 10.4103/CRST.CRST_119_20.
Mohile SG, Dale W, Somerfield MR, et al. Practical Assessment and Management of Vulnerabilities in Older Patients Receiving Chemotherapy: ASCO Guideline for Geriatric Oncology. J Clin Oncol 2018;36(22):2326–47. doi: 10.1200/JCO.2018.78.8687.
Bellera CA, Rainfray M, Mathoulin-Pélissier S, et al. Screening older cancer patients: first evaluation of the G-8 geriatric screening tool. Ann Oncol 2012;23(8):2166–72. doi: 10.1093/annonc/mdr587.
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. doi: 10.1001/jama.1963.03060120024016.
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. doi: 10.1016/0021-9681(87)90171-8.
ShumwayCook A, Brauer S, Woollacott M. Predicting the probability for falls in communitydwelling older adults using the Timed Up and Go Test. Phys Ther 2000;80:896–903. PMID: 10960937.
Tiwari SC, Tripathi RK, Kumar A. Applicability of the Mini-mental State Examination (MMSE) and the Hindi Mental State Examination (HMSE) to the urban elderly in India: a pilot study. Int Psychogeriatr 2009;21(1):123–8. doi: 10.1017/S1041610208007916.
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 DSMIV. Int J Geriatr Psychiatry 1999;14:858 – 65. doi: 10.1002/(sici)1099-1166(199910)14:10<858::aid-gps35>3.0.co;2-8.
Vellas B, Guigoz Y, Garry PJ, et al. The Mini Nutritional Assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition 1999;15:116–22. doi: 10.1016/s0899-9007(98)00171-3.
Linn BS, Linn MW, Gurel L. Cumulative illness rating scale. J Am Geriatr Soc 1968;16(5):622–6. doi: 10.1111/j.1532-5415.1968.tb02103.x.
Hurria A, Mohile S, Gajra A, et al. Validation of a Prediction Tool for Chemotherapy Toxicity in Older Adults With Cancer. J Clin Oncol 2016;34(20):2366–71. doi: 10.1200/JCO.2015.65.4327.
Aaldriks AA, Giltay EJ, le Cessie S, et al. Prognostic value of geriatric assessment in older patients with advanced breast cancer receiving chemotherapy. Breast 2013;22(5):753–60. doi: 10.1016/j.breast.2013.01.011.
Aaldriks AA, van der Geest LG, Giltay EJ, et al. Frailty and malnutrition predictive of mortality risk in older patients with advanced colorectal cancer receiving chemotherapy. J Geriatr Oncol 2013;4(3):218–26. doi: 10.1016/j.jgo.2013.04.001.
Ferrat E, Paillaud E, Laurent M, et al; ELPACA Study Group. Predictors of 1-Year Mortality in a Prospective Cohort of Elderly Patients With Cancer. J Gerontol A Biol Sci Med Sci 2015;70(9):1148–55. doi: 10.1093/gerona/glv025.
Morley JE, Thomas DR. Anorexia and aging: pathophysiology. Nutrition 1999;15(6):499–503.
Ezeoke CC, Morley JE. Pathophysiology of anorexia in the cancer cachexia syndrome. J Cachexia Sarcopenia Muscle 2015;6(4):287–302. doi: 10.1016/s0899-9007(99)00057-x.
Dos Santos M, Licaj I, Bellera C, et al. Cognitive Impairment in Older Cancer Patients Treated with First-Line Chemotherapy. Cancers (Basel). 2021;13(24):6171. doi: 10.3390/cancers13246171.
Donini LM, Savina C, Cannella C. Eating habits and appetite control in the elderly: the anorexia of aging. Int Psychogeriatr 2003;15(1):73–87. doi: 10.1017/s1041610203008779.
Parrino S, Sola M, Giulio B, et al. Evaluation depression in elderly patients with cancer. Ann Oncol 2017;28(S6):vi82. doi: https://doi.org/10.1093/annonc/mdx434.001.
Borza T, Harneshaug M, Kirkhus L, et al. The course of depressive symptoms and mortality in older patients with cancer. Aging Ment Health. 2022;26(6):1153–60. doi: 10.1080/13607863.2021.1932739.
Kenis C, Decoster L, Bastin J, et al. Functional decline in older patients with cancer receiving chemotherapy: A multicenter prospective study. J Geriatr Oncol.2017;8(3):196–205. doi: 10.1016/j.jgo.2017.02.010.
Owusu C, Margevicius S, Schluchter M, Koroukian SM, Berger NA. Short Physical Performance Battery, usual gait speed, grip strength and Vulnerable Elders Survey each predict functional decline among older women with breast cancer. J Geriatr Oncol 2017;8(5):356–62. doi: 10.1016/j.jgo.2017.07.004.

No competing interests reported.

Download PDF

Reviewers invited by journal
12 Sep, 2024
Editor assigned by journal
12 Sep, 2024
Submission checks completed at journal
05 Aug, 2024
First submitted to journal
31 Jul, 2024

You are reading this latest preprint version

High prevalence of malnutrition in geriatric patients with solid organ cancer: An institutional study

Status:

Version 1

Abstract

INTRODUCTION

PATIENTS AND METHODS

RESULTS

BMI : Body-Mass Index; COPD: Chronic Obstructive Pulmonary Disease

Correlation of MNA scores with other domains/risk factors

DISCUSSION

CONCLUSION

Declarations

Funding statement

Conflict of interest disclosure
There are no conflicts of interest to disclose.

Ethics approval statement
Approved by the Institutional Ethics Committee letter no : AIIMS/IEC/22/129.

Author Contribution

Acknowledgement:

Data availability statement:

References

Additional Declarations

Status:

Version 1

High prevalence of malnutrition in geriatric patients with solid organ cancer: An institutional study

Status:

Version 1

Abstract

INTRODUCTION

PATIENTS AND METHODS

RESULTS

BMI : Body-Mass Index; COPD: Chronic Obstructive Pulmonary Disease

Correlation of MNA scores with other domains/risk factors

DISCUSSION

CONCLUSION

Declarations

Funding statement

Conflict of interest disclosure There are no conflicts of interest to disclose.

Ethics approval statement Approved by the Institutional Ethics Committee letter no : AIIMS/IEC/22/129.

Author Contribution

Acknowledgement:

Data availability statement:

References

Additional Declarations

Status:

Version 1

Conflict of interest disclosure
There are no conflicts of interest to disclose.

Ethics approval statement
Approved by the Institutional Ethics Committee letter no : AIIMS/IEC/22/129.