Geriatric impairments are prevalent and predictive of survival in older patients with cancer receiving radiotherapy: a prospective observational study

Figures & data

Table 1. Domains in the modified geriatric assessment (mGA) and definitions of impairments.

Domain	Assessment	Rated by	Variable name	Scores and range	Interpretation	Cut-off values for impairment	Rationale for cut-off values
Comorbidity	Charlson Comorbidity Index	Patient/ Nurse	CCI	0-26 (continuous)	Higher score = more comorbidity	≥2	Recommendations by Charlson et al. 1987 [24], Sundarajan et al. 2004 [25].
Medications	Registration of regular medications by ATC^a system	Nurse	Medications	Number of daily medications		≥5	Cut-off is frequently used in the literature, Gutiérrez-Valencia et al. 2018 [34], Mohile et al. 2020 [33].
Nutritional status	Mini Nutritional Assessment Short Form	Nurse	MNA-SF	0-14 (continuous)	Higher score = better nutritional status	≤11	Cut-off point for "at risk of malnutrition" suggested by Kaiser et al. 2009 [27].
Mobility	Timed Up and Go	Nurse	TUG	Number of seconds (continuous)		≥14	Similar cut-off used by Mohile et al. 2020 [33], Jolly et al. 2015 [36], Owusu et al. 2011 [37].
Falls the last six months	Registration of number of falls	Patient	Falls	0-1 or ≥ 2 (dichotomised)		≥2	Similar cut-off used by Owusu et al. 2011 [37], Jolly et al 2015 [36].
Basic activities of daily living (ADL)	Barthel Index	Patient	Barthel	0-20 (continuous)	Higher score =  better function	˂19	Similar cut-off used by Kristjansson et al. 2010 [38].
Instrumental activities of daily living (IADL)	Nottingham Extended Activities of Daily Living	Patient	NEADL	0-66 (continuous)	Higher score =  better function	˂44	Similar cut-off used by Kristjansson et al. 2010 [38].
Cognitive function	Montreal Cognitive Assessment test	Nurse	MoCA	0-30 (continuous)	Higher score = better function	65-75 years  ≤ 23  > 75 years  ≤ 21	Based on interpretation of Borland et al. 2017 [35].
Depressive symptoms	Geriatric Depression Scale	Patient	GDS	0-15 (continuous)	Higher score = more depressive symptoms	≥5	Cut-off recommended by Pocklington et al. 2016 [39], Mohile et al. 2020 [33].

^aAnatomical Therapeutic Chemical Classification System.

Table 2. Baseline patient characteristics.

	Total	Curative RT	Palliative RT
	N = 301 (100%)	N = 162 (53.8%)	N = 139 (46.2%)
Age
Mean (SD)	73.6 (6.3)	72.5 (6.1)	74.9 (6.4)
Gender, female, n (%)	142 (47.2)	92 (56.8)	50 (36.0)
Cancer type, n (%)
Breast	95 (31.6)	82 (50.6)	13 (9.4)
Prostate	73 (24.3)	51 (31.5)	22 (15.8)
Lung	65 (21.6)	15 (9.3)	50 (36.0)
Other	68 (22.6)	14 (8.6)	54 (38.8)
ECOG PS, n (%)
0–1	256 (85.0)	155 (95.7)	101 (72.7)
2–4	45 (15.0)	7 (4.3)	38 (27.3)
Stage, n (%)
I	62 (20.6)	62 (38.3)	0
II	42 (14.0)	39 (24.1)	3 (2.2)
III	78 (25.9)	61 (37.7)	17 (12.2)
IV	119 (39.5)	0	119 (85.6)^a
Distant metastasis, n (%)
No	188 (62.5)	162 (100%)	26 (18.7)
Yes	113 (37.5)	0	113 (81.3)
Metastasis location, n (%)
ymph	35 (11.6)	NA	35 (25.2)
Brain	14 (4.7)	NA	14 (10.1)
Liver	17 (5.7)	NA	17 (12.2)
Lunge	26 (8.6)	NA	26 (18.7)
Skeleton	77 (25.6)	NA	77 (55.4)
Other sites	30 (10.0)	NA	30 (21.6)
Time from diagnosis to inclusion (months)
Median (min–max)	5.1 (0–282.2)	3.8 (0.4–153.5)	15.8 (0–282.2)
Radiation field, n (%)
Brain/head	18 (6.0)	0	18 (12.9)
Skin face/head/neck	12 (4.0)	8 (4.9)	4 (2.9)
Soft tissue breast region	133 (44.2)	95 (58.6)	38 (27.3)
Soft tissue pelvic/abd. region	75 (24.9)	58 (35.8)	17 (12.2)
Vertebrae skeleton	35 (11.6)	0	35 (25.2)
Pelvic skeleton	15 (5.0)	0	15 (10.8)
Skeleton other sites	23 (7.6)	0	23 (16.5)
Other sites	6 (2.0)	1 (0.6)	5 (3.6)
Total radiation dose (Gy)
Median (min–max)	40.0 (4.0–78.0)	45.5 (4.0–78)	30.0 (8.0–60.0)
Dose per fraction (Gy)
Median (min–max)	2.7 (1.0–8.0)	2.7 (1.5–4.6)	3.0 (1.0–8.0)
Number of fractions
Median (min–max)	14.8 (1–39)	17.8 (2–39)	10 (1–30)
Previous treatment, n (%)
Radiotherapy	39 (13.0)	2 (1.2)	37 (26.6)
Surgery	173 (57.5)	108 (66.7)	65 (46.8)
Chemotherapy	80 (26.6)	26 (16.0)	54 (38.8)
Endocrine	57 (18.9)	28 (17.3)	29 (20.9)
Other systemic treatment	28 (9.3)	2 (1.2)	26 (18.7)
None	58 (19.3)	27 (16.7)	31 (22.3)
Concomitant systemic treatment, n (%)
No	187 (62.1)	105 (64.8)	82 (59.0)
Yes	114 (37.9)	57 (35.2)	57 (41.0)
Type of concomitant systemic treatment
Chemotherapy	29 (9.6)	9 (5.6)	20 (14.1)
Endocrine	74 (24.6)	48 (29.6)	26 (18.7)
Other systemic treatment	30 (10.0)	8 (4.9)	22 (15.8)

RT: radiotherapy; SD: standard deviations; ECOG PS: Eastern Cooperative Oncology Group Performance Status; abd: abdominal; Gy: Grey.

^aSix patients receiving palliative treatment were classified as having stage IV disease without the presence of distant metastasis, among whom four had glioblastoma and two had lymphoma.

Table 3. Mean scores in mGA domains and proportions of patients with geriatric impairments according to treatment intent.

	Total	Curative RT	Palliative RT	p Value^a	Total no. (%) with impairments	No. (%) receiving curative RT with impairments	No. (%) receiving palliative RT with impairments
	N = 301	N = 162	N = 139		N = 301	N = 162	N = 139
CCI
n	301	162	139		82 (27.2)	33 (20.4)	49 (35.3)
Mean (SD)	1.1 (1.3)	0.8 (1.1)	1.4 (1.5)	.001^b
Medications
n	301	162	139		166 (55.1)	72 (44.4)	94 (67.6)
Mean (SD)	5.5 (3.6)	4.5 (3.3)	6.6 (3.6)	p ˂ .001^b
MNA-SF
n	301	162	139		167 (55.5)	56 (34.6)	111 (79.9)
Mean (SD)	10.6 (2.3)	11.6 (1.9)	9.5 (2.3)	p ˂ .001^b
TUG
n	282	161	121		64 (21.3)	17 (10.5)	47 (33.8)
Mean (SD)	10.6 (5.7)	9.5 (5.6)	12.0 (5.5)	p ˂ .001^b
Missing	19	1	18		0^d	0^d	0^d
Falls
n	301	162	139		34 (11.3)	15 (9.3)	19 (13.7)
0 or 1, n(%)	267 (88.7)	147 (90.7)	120 (86.3)
≥ 2, n (%)	34 (11.3)	15 (9.3)	19 (13.7)	.228^c
IADL - NEADL
n	298	161	137		63 (21.1)	17 (10.6)	46 (33.6)
Mean (SD)	53.2 (14.0)	58.3 (10.4)	47.0 (15.2)	p ˂ .001^b
Missing	3	1	2		3	1	2
ADL- Barthel
n	301	162	139		60 (19.9)	16 (9.9)	44 (31.7)
Mean (SD)	19.0 (2.2)	19.5 (1.3)	18.5 (2.8)	p ˂ .001^b
MoCA
n (total)	298	162	136
n = 65-75 years	198	120	78		66 (33.3)	29 (24.2)	37 (47.4)
n > 75 years	100	42	58		39 (39.0)	16 (38.1)	23 (39.7)
Mean (SD)	24.0 (3.7)	24.8 (3.4)	23.0 (3.8)	p ˂ .001^b
Missing	3	0	3
GDS
n	301	162	139		63 (20.9)	24 (14.8)	39 (28.1)
Mean (SD)	2.9 (2.6)	2.2 (2.2)	3.7 (2.7)	p ˂ .001^b
No. of mGA impairments
Median (min–max)	2.0 (0-9)	1.0 (0-9)	3 (0-9)
0, n (%)	49 (16.3)	41 (25.3)	8 (5.8)
1, n (%)	67 (22.3)	49 (30.2)	18 (12.9)
2, n (%)	50 (16.6)	28 (17.3)	22 (15.8)
3, n (%)	48 (15.9)	20 (12.3)	28 (20.1)
≥4, n (%)	81 (26.9)	23 (14.2)	58 (41.8)
Missing, n (%)	6 (2.0)	1 (0.7)	5 (3.6)

RT: radiotherapy; mGA: modified geriatric assessment

^ap Values represent results of tests assessing differences in mean score between curative and palliative patients.

^bindependent samples t-test.

^cχ²- test.

^dPatients who were not able to perform TUG have been classified as having an impairment.

Figure 1. Kaplan-Meier curves for overall survival (months) according to (a) treatment intent (curative or palliative), (b) the number of geriatric impairments (0, 1, 2, 3, ≥4).

Table 4. Cox regression analyses of the association between mGA domains and overall survival, N = 295.

Covariates/ mGA domain	Unadjusted		Adjusted
	HR (95% CI)	p Value	Regr. Coeff. (SE) / HR (95% CI)	p Value
Treatment intent
Curative– ref.	1		0
Palliative	19.40 (10.85; 34.68)	<.001	4.46 (1.06)	<.001
Age	1.04 (1.02; 1.07)	.002	1.00 (0.97; 1.04)	.932
Gender (Male – ref.)	0.57 (0.39; 0.82)	.002	0.73 (0.45; 1.17)	.188
CCI	1.26 (1.13; 1.40)	<.001	0.97 (0.85; 1.10)	.614
Medications	1.16 (1.11; 1.22)	<.001	1.05 (0.99; 1.12)	.126
MNA-SF	0.73 (0.68; 0.79)	<.001	0.90 (0.81; 0.99)	.038
TUG^a	9 × 10^-8 (2 × 10^-9;4 × 10^-6)	<.001	1.73 (0.002; 1549.0)	.875
Falls (0-1– ref.)	1.50 (0.91; 2.47)	.113	0.68 (0.38; 1.23)	.200
NEADL	0.95 (0.94; 0.96)	<.001	0.98 (0.95; 1.00)	.027
MoCA	0.89 (0.86; 0.93)	<.001	0.99 (0.93; 1.05)	.788
GDS-15	1.16 (1.10; 1.23)	<.001	0.99 (0.92; 1.07)	.822
Interaction term	Regr. Coeff. (SE)	p Value	Regr. Coeff. (SE)	p Value
Treatment intent
(Curative ref.)	4.89 (1.05)	<.001
Cancer type
Breast – ref.
Prostate	0.47 (1.41)	.739	0.32 (1.44)	.825
Lung	3.92 (1.07)	<.001	3.79 (1.09)	<.001
Other	3.25 (1.12)	.004	2.76 (1.15)	.016
Treatment intent, palliative x cancer type
Breast – ref.
Prostate	−0.73 (1.47)	.620	−0.91 (1.48)	.538
Lung	−3.71 (1.13)	.001	−3.66 (1.14)	.001
Other	−3.33 (1.17)	.004	−2.83 (1.19)	.017

^aTUG values are inverted. The 19 patients with missing TUG were assigned the value 0 (i.e., they used indefinitely long time).

Table 5. Explorative cox regression analyses of the association between ECOG PS and overall survival, N = 295.

Covariate	Unadjusted		Adjusted
	HR (95% CI)	p Value	Regr. Coeff. (SE) / HR (95% CI)	p Value
Treatment intent
Curative – ref.	1		0
Palliative	19.40 (10.85; 34.68)	<.001	4.89 (1.05)	<.001
Age	1.04 (1.02; 1.07)	.002	1.01 (0.98; 1.04)	.447
Gender	0.57 (0.39; 0.82)	.002	0.81 (0.52; 1.27)	.358
ECOG PS (0-1 – ref.)	3.70 (2.47; 5.53)	<.001	1.71 (1.12; 2.62)	.012
Interaction term	Regr. Coeff. (SE)	p Value	Regr. Coeff. (SE)	p Value
Treatment intent
(Curative – ref.)	4.89 (1.05)	<.001
Cancer type
Breast – ref.
Prostate	0.47 (1.41)	.739	0.30 (1.43)	.832
Lung	3.92 (1.07)	<.001	3.81 (1.08)	<.001
Other	3.25 (1.12)	.004	2.97 (1.15)	.010
Treatment intent, Palliative x cancer type
Breast – ref.
Prostate	−0.73 (1.47)	.620	−0.95 (1.47)	.520
Lung	−3.71 (1.13)	.001	−3.88 (1.13)	.001
Other	−3.33 (1.17)	.004	−3.25 (1.18)	.006

mGA: modified geriatric assessment; HR: hazards ratio; CI: confidence interval; Regr.Coeff: regression coefficient; SE: standard error; ref: reference; CCI: Charlson Comorbidity Index; MNA-SF: Mini Nutritional Assessment Short Form; TUG: Timed Up and Go; NEADL: Nottingham Extended Activities of Daily Living; MoCA: Montreal Cognitive Assessment test; GDS-15: Geriatric Depression Scale-15; ECOG PS: Eastern Cooperative Oncology Group Performance Status.

Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–383.

 PubMedGoogle Scholar

Sundararajan V, Henderson T, Perry C, et al. New ICD-10 version of the charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol. 2004;57(12):1288–1294.

 PubMed Web of Science ®Google Scholar

Gutiérrez-Valencia M, Izquierdo M, Cesari M, et al. The relationship between frailty and polypharmacy in older people: a systematic review. Br J Clin Pharmacol. 2018;84(7):1432–1444.

 PubMed Web of Science ®Google Scholar

Mohile SG, Epstein RM, Hurria A, et al. Communication with older patients with cancer using geriatric assessment: a Cluster-Randomized clinical trial from the national cancer institute community oncology research program. JAMA Oncol. 2020;6(2):196–204.

 PubMed Web of Science ®Google Scholar

Kaiser MJ, Bauer JM, Ramsch C, MNA-International Group, et al. Validation of the mini nutritional assessment short-form (MNA-SF): a practical tool for identification of nutritional status. J Nutr Health Aging. 2009;13(9):782–788.

 PubMed Web of Science ®Google Scholar

Jolly TA, Deal AM, Nyrop KA, et al. Geriatric assessment-identified deficits in older cancer patients with normal performance status. Oncologist. 2015;20(4):379–385.

 PubMed Web of Science ®Google Scholar

Owusu C, Koroukian SM, Schluchter M, et al. Screening older cancer patients for a comprehensive geriatric assessment: a comparison of three instruments. J Geriatr Oncol. 2011;2(2):121–129.

 PubMed Web of Science ®Google Scholar

Kristjansson SR, Jordhøy MS, Nesbakken A, et al. Which elements of a comprehensive geriatric assessment (CGA) predict post-operative complications and early mortality after colorectal cancer surgery? Journal of Geriatric Oncology. 2010;1(2):57–65.

 Web of Science ®Google Scholar

Borland E, Nägga K, Nilsson PM, et al. The montreal cognitive assessment: Normative data from a large swedish Population-Based cohort. JAD. 2017;59(3):893–901.

 Web of Science ®Google Scholar

Pocklington C, Gilbody S, Manea L, et al. The diagnostic accuracy of brief versions of the geriatric depression scale: a systematic review and Meta-analysis. Int J Geriatr Psychiatry. 2016;31(8):837–857.

 PubMed Web of Science ®Google Scholar