Vol 19, No 6 (2023)
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Comprehensive geriatric assessment and clinical outcomes of frail older adults with diffuse large B-cell lymphoma: a meta-analysis

Teodoro J. Oscanoa123, Xavier Vidal4, Brady E. Beltran25, Roman Romero-Ortuno67
Oncol Clin Pract 2023;19(6):398-412.

Abstract

Introduction. Comprehensive geriatric assessment (CGA) is used to personalize cancer treatments in frail older adults. However, its utility to guide treatments in frail older patients with diffuse large B-cell lymphoma (DLBCL) is not well known. We performed a meta-analysis of evidence published in this area. 

Material and methods. We searched PubMed and Google Scholar for studies published between January 2000 and January 2023 that included patients aged ≥ 65 years with a diagnosis of DLBCL who underwent CGA before treatment (CGA-modulated studies) and who did not (non-CGA-modulated studies). We evaluated clinical outcomes in frail/unfit patients in terms of complete response (CR), incidence of grade ≥ 3 toxicity, and 2-year overall survival (OS) in both types of studies. 

Results. Fifteen studies [8 CGA-modulated (n = 733, median age 76, 54% male, 52% frail/unfit) and 7 non-CGA-modulated (n = 2447, median age 76, 52% male, 32% frail/unfit)] were included. In the CGA-modulated studies, the CR proportion of frail/unfit patients was 34% (95% CI 23–46%) vs. 28% (95% CI 19–38%) in the non-CGA-modulated studies (p = 0.436). Grade 3–4 hematological toxicity in frail/unfit patients was 26% (95% CI 5–55%) vs. 36% (95% CI 13–63%) (p = 0.583), respectively. Two-year OS of frail/unfit patients was 52% (95% CI 38–66%) vs. 27% (95% CI 19–36%) (p = 0.003), respectively. 

Conclusions. Although the proportion of frail/unfit patients was lower in non-CGA-modulated studies, CGA-modulated studies reported higher OS. CGA could be useful to guide the treatment plan in older patients with DLBCL. Randomized clinical trials with standardized CGA instruments are necessary to confirm these findings.

REVIEW ARTICLE

Oncology in Clinical Practice

DOI: 10.5603/OCP.2023.0021

Copyright © 2023 Via Medica

ISSN 2450–1654

e-ISSN 2450–6478

Comprehensive geriatric assessment and clinical outcomes of frail older adults with diffuse large B-cell lymphoma: a meta-analysis

Teodoro J. Oscanoa123Xavier Vidal4Brady E. Beltran25Roman Romero-Ortuno67
1Universidad Nacional Mayor de San Marcos, Facultad de Medicina, Lima, Perú
2Universidad de San Martín de Porres, Facultad de Medicina Humana, Lima, Perú
3Geriatric Department, Almenara Hospital, ESSALUD, Lima, Perú
4Clinical Pharmacology,Vall d’Hebron University Hospital, Barcelona, Spain
5Department of Oncology and Radiotherapy, Hospital Nacional Edgardo Rebagliati Martins, ESSALUD, Lima, Perú
6Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
7Global Brain Health Institute, Trinity College Dublin, Ireland

Address for correspondence:

Teodoro J. Oscanoa PhD

Universidad de San Martín de Porres,

Facultad de Medicina Humana, Drug Safety

Research Center

Av. Alameda del Corregidor 1502,

La Molina 15024. Lima, Perú

e-mail: tjoscanoae@gmail.com;
toscanoae@usmp.pe

Received: 15.03.2023 Accepted: 19.06.2023 Early publication date: 07.08.2023

ABSTRACT

Introduction. Comprehensive geriatric assessment (CGA) is used to personalize cancer treatments in frail older adults. However, its utility to guide treatments in frail older patients with diffuse large B-cell lymphoma (DLBCL) is not well known. We performed a meta-analysis of evidence published in this area.

Material and methods. We searched PubMed and Google Scholar for studies published between January 2000 and January 2023 that included patients aged65 years with a diagnosis of DLBCL who underwent CGA before treatment (CGA-modulated studies) and who did not (non-CGA-modulated studies). We evaluated clinical outcomes in frail/unfit patients in terms of complete response (CR), incidence of grade3 toxicity, and 2-year overall survival (OS) in both types of studies.

Results. Fifteen studies [8 CGA-modulated (n = 733, median age 76, 54% male, 52% frail/unfit) and 7 non-CGA-modulated (n = 2447, median age 76, 52% male, 32% frail/unfit)] were included. In the CGA-modulated studies, the CR proportion of frail/unfit patients was 34% (95% CI 2346%) vs. 28% (95% CI 1938%) in the non-CGA-modulated studies (p = 0.436). Grade 34 hematological toxicity in frail/unfit patients was 26% (95% CI 555%) vs. 36% (95% CI 1363%) (p = 0.583), respectively. Two-year OS of frail/unfit patients was 52% (95% CI 3866%) vs. 27% (95% CI 1936%) (p = 0.003), respectively.

Conclusions. Although the proportion of frail/unfit patients was lower in non-CGA-modulated studies, CGA-modulated studies reported higher OS. CGA could be useful to guide the treatment plan in older patients with DLBCL. Randomized clinical trials with standardized CGA instruments are necessary to confirm these findings.

Keywords: comprehensive geriatric assessment, diffuse large B-cell lymphoma, frailty, meta-analysis, older adults, outcomes

Oncol Clin Pract 2023; 19, 6: 398412

Introduction

Diffuse large B-cell lymphoma (DLBCL) is the most frequent type of malignant lymphoma and constitutes about 40% of non-Hodgkin lymphoma (NHL) cases. The mean age at onset is 65 years, and its incidence increases with age [1]. The standard therapeutic regimen is 6 courses of combined therapy with rituximab and CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisolone). The 5-year overall survival (OS) rate is 5060%, and complete response (CR) and 5-year OS decrease with age [2].

Prognostic scores such as the International Prognostic Index (IPI) have been adopted in DLBCL patients. Among other criteria such as disease stage, the IPI considers older chronological age ( > 60 years) and worse performance status [Eastern Cooperative Oncology Group (ECOG) Performance Status > 2] as markers of higher risk [3–5]. Rituximab-CHOP (R-CHOP) is standard first-line therapy. However, about 40% of older patients do not tolerate the standard dose of R-CHOP due to such causes as comorbidities, malnutrition, and the presence of other geriatric syndromes [6]. Frailty is defined as physiological vulnerability to stressors, is more related to biological than chronological age [7], and encapsulates many of the systemic dysregulations that are associated with poorer outcomes in geriatric oncology [8].

In frail older adults, the application of comprehensive geriatric assessment (CGA) has been shown to improve outcomes in the acute general hospital setting [9]. This is because CGA is a multidisciplinary diagnostic and treatment process that identifies medical, psychosocial, and functional capabilities of older adults to develop a coordinated plan to maximize overall health with aging [2]. Therefore, by performing a CGA, the frailty status of an older adult can be improved, conferring more resilience before he/she experiences a planned stressor. This has been exemplified in prehabilitation of frail older adults undergoing elective surgery [10]. Some abbreviated CGA tools have been made available for implementation in research studies [11].

Comprehensive geriatric assessment is used to personalize cancer treatments in frail older adults. However, its utility to guide treatments in frail older DLBCL patients is not well known [12]. We performed a meta-analysis of evidence published in this area, with a specific aim to compare the outcomes of non-CGA-modulated studies versus CGA-modulated studies, in terms of CR, incidence of grade3 toxicity, and 2-year OS.

Material and methods

We searched PubMed, Google Scholar, and the Cochrane Database of Systematic Reviews for studies including DLBCL patients aged above 64 years. The research period ranged from January 2000 to January 2023. Case reports, editorials, comments, and reviews were excluded. Our study followed the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) [13] (Tab. S1 in supplementary file).

Search strategy

The search terms were “Comprehensive geriatric assessment”, “diffuse large B-cell lymphoma”, “chemotherapy”, “immunochemotherapy”, “Humanized anti-CD19 CART”, and “frailty”.

Inclusion criteria

Studies that met the following criteria were included a) patients equal to or older than 65 years and diagnosed with DLBCL; b) CGA was used to categorize patients into fit or unfit/frail, prospectively or retrospectively. “CGA-modulated studies” were those in which CGA was used to select patients (frail/unfit or fit) for a specific chemotherapy scheme. Those in whom this criterion was not used to qualify them for specific chemotherapy or was done retrospectively were called “non-CGA-modulated studies”; c) Studies reported clinical outcome data such as overall survival (OS), complete response (CR), and the incidence of at least grade 3 hematological toxicity [14].

Quality assessment

The quality of the studies was appraised according to the Reporting of Observational Studies in Epidemiology (STROBE) [15].

Statistical analyses

Outcomes of CGA-modulated studies were compared to those of non-CGA-modulated studies in frail/unfit patients. The statistical comparison of proportions was carried out with the Chi-square statistic.

When possible, overall estimates in the pooled analysis were obtained using Stata 13 software (Stata Corp LP, College Station, TX) and the Meta XL (www.epigear.com) add-in for Microsoft Excel [12]. A pooled prevalence was calculated with 95% confidence interval (CI) by combining estimates from selected studies based on a random-effects model [13]; this is a variant of the inverse of the variance method, and it incorporates intra- and inter-variability of studies. Heterogeneity between estimates was assessed using the I2 statistic, which describes the percentage of variation across studies not caused by sampling error [16]. To perform the meta-analysis of two-year OS of frail/unfit patients in the studies, only those studies that reported such outcomes were selected.

Results

After screening 814 citations, 15 studies (8 cohort and 7 non-randomized clinical trials) were included (Fig. 1). The total number of patients was 3180, mean age 76.4 ± 4.1 years, and 53.2% were male. Eight studies were carried out in Italy [17–24], 3 in China [25–27], 1 in Australia [28], 1 in Japan [29], 1 in Mexico [30], and 1 in Norway [31] (Tab. 1).

Figure 1. Study flowchart; CGA comprehensive geriatric assessment
Table 1. Characteristics of included studies

Study

Country

Type of study

Age [median]

Sex
[male %]

Number of patients

Prevalence
of frailty [%]

Frailty
criteria

Categories

Quality assessment: STROBE [%]

CGA-modulated studies

Xu et al. (2022)

China

Non-randomized clinical trial

80

77

30

80

sCGA

Fit, unfit, frail

96.7

Bocci et al. (2022)

Italy

Non-randomized clinical trial

84

64

22

99

sCGA

Unfit, frail,
“superfrail”

93.3

Bai et al. (2020)

China

Non-randomized clinical trial

69

57.7

78

36

sCGA

Fit, unfit, frail

76.6

Storti et al. (2018)

Italy

Non-randomized clinical trial

81

58

45

99

sCGA

Frail

90

Lastra-German et al. (2018)

Mexico

Cohort

70

42.9

49

41

Phenotype

Fit, unfit, frail

83.3

Merli et al. (2013)

Italy

Non-randomized clinical trial

78

43

318

29.6

sCGA

Fit, Frail

90

Spina et al. (2012)

Italy

Non-randomized clinical trial

75

41

100

13

sCGA

Fit, unfit, frail

90

Olivieri et al. (2012)

Italy

Cohort

74

50.5

91

16

sCGA

Fit, patients with comorbidities, frail

83.3

non-CGA-modulated studies

Tanaka et al. (2022)

Japan

Cohort

79

52.6

78

53

Full CGA

Independent, dependent

80

Zhang et al. (2022)

China

Non-randomized clinical trial

73

52

31

13

sCGA

Fit, unfit, frail

83.3

Merli et al. (2021)

Italy

Cohort

76

50

1207

18

sCGA

Fit, unfit, frail

90

Isaksen et al. (2021)

Norway

Cohort

79

52

747

34

full CGA

Fit, unfit, frail

90

Ong et al. (2019)

Australia

Cohort

73

55.8

138

38

sCGA

Fit, unfit, frail

96.7

Tucci et al. (2015)

Italy

Cohort

77

52.6

173

38

sCGA

Fit, unfit, frail

90

Marchesi et al. (2013)

Italy

Cohort

78

49.32

73

28.77

sCGA

Fit, intermediate, frail

90

For the categorization of patients according to CGA, simplified CGA (sCGA) was used in 80% of the studies [17–28], full CGA [29, 31] in 13.3%, and the frailty phenotype model [30] in 6.7%. The instruments used for CGA and operational criteria for the identification of frail/unfit and fit patients are in Table S1 in the supplementary file. One study only included frail patients [20] (Tab. 1).

The prevalence of frail, unfit, and fit patients was 32% (95% CI 2540), 27% (95% CI 2132), and 47% (95% CI 3858), respectively.

Eight studies were CGA-modulated (n = 733, median age 76, 54% male, 52% frail/unfit) and 7 non-CGA-modulated (n = 2447, median age 76, 52% male, 32% frail/unfit) (Tab. 2).

Table 2. Treatment, comprehensive geriatric assessment, and outcomes for frail older adults with diffuse large B-cell lymphoma

Studies

Treatment

Complete
response (CR)

Overall survival (OS)

Event-free survival (EFS)/progression-
-free survival (PFS)

Treatment-related mortality (TRM)

Adverse drug reaction (ADR)

CGA-modulated studies

Xu et al. (2022)

Unfit or frail: ibrutinib, rituximab,
lenalidomide

Complete response rate: Unfit/frail: 56.7% (95% CI 37.474.5), overall response: 66.7% (95% CI 47.282.7)

2 years: Unfit/Frail (66.7%; 95% CI 46.980.5)

PFS: 2 years: 53.3% (95% CI 34.3-69.1)

Missing

Hematological grade 34 toxicity: neutropenia (23%) thrombocytopenia (10%), and anemia (7%)

Bocci et al. (2022)

Metronomic all-oral DEVEC [prednisolone/deltacortene, vinorelbine (VNR),
etoposide (ETO), cyclophosphamide]
combined with i.v. rituximab (R)

Overall response (ORR) and complete remission rate (CRR): 64%

2 years: frail: 54% (95% CI 3272)

EFS: 54% (95% CI = 32––72)

Missing

Treatment-related serious adverse events (27%)

Bai et al. (2020)

Fit: R-CHOP, unfit + frail: R-CHOP with
reduced dose of anthracycline, R-CVP,
or R-miniCHOP

Fit (84.4%), unfit + frail (51.5%) (p = 0.002)

2 years: fit (98%), unfit + frail (69%) (p = 0.0013). 3 years: fit (91%), unfit + frail (69%) (p = 0.021)

2 years PFS: fit (72%), unfit + frail (69%) (p = 0.77). 3 years PFS: fit (72%), unfit + frail (35%) (p = 0.0013)

0%

Hematological grade 34 toxicity: fit (51.1%),
unfit + frail (54.5%) (p > 0.05).

Storti et al. (2018)

Frail: bendamustine and rituximab

Frail: 53%

2 years: Frail (51%)

The median progression-free survival: 10 months

Missing

Total grade 34 toxicity (51.1%). Hematological grade 34 toxicity 46.7%). Non-hematologicalal grade 34 toxicity (15.6%)

Lastra-German
et al. (2018)

Fit: R-CHOP, unfit: R-CHOP, frail: R-COP

Fit (66.6%), unfit (78.3%), frail (40.0%) (p = 0.121)

2 years: fit (87%, unfit (82%), frail (59%) (p = 0.159)

Mean 2-year disease-free survival (DFS): frail (87%), fit (100%) (p = 0.287).

Missing

Grade 34 hematological toxicity: fit (83.3%), unfit (65.2%), frail (45%) (p = 0.192). Nonhematological toxicity: fit (33%), unfit (65%), frail = 70%. (p = 0.445)

Merli et al. (2013)

Treatment of frail patients: polychemotherapy with anthracyclines (includes CHOP, mini-CEOP, CNOP, P-VEBEC); polychemotherapy without anthracyclines (includes CVP); mono-chemotherapy, radiotherapy, palliation

NR

Worse OS, hazard ratio: frail vs. fit: 3.09 (95% CI 2.2
–4.33; p < 0.001)

NR

NR

Treatment-related complications/toxicity (22% of deaths, 18% of treated patients)

Spina et al. (2012)

A. No comorbidities: rituximab ± CHOP; Mild cardiopathy (NYHA class II or CIRS-G grade 2): R ± CEOP; Severe cardiopathy (NYHA class III/IV or CIRS-G grade3): R ± CVP

B. 100%, if ADL 6 or IADL 78; 75%,
if ADL 5 or IADL 6; % (p = 0.11) 50%,
if ADL < 5 or IADL < 5

Fit (85%), unfit (72%),
frail (85%) (p = 0.34); > 80 y
(83%); all (70.6%)

5 years: fit (76%), unfit (53%;), frail (29%) (p = 0.001)

5y EFS: 80% ( > 80 y: 67%, p = 0.96); 5 y EFS: 52% ( > 80 y: 46%, p = 0.06)

4%

Total grade 34 toxicity: fit (31%), unfit (48%), frail
(58%) (p = 0.11). Toxic deaths (5%, 9%, and 11%, respectively) (p > 0.05)

Olivieri et al. (2012)

Fit: R-CHOP, intermediate: R-CDOP,
frail: Mini-CHOP

Fit (81.5%), patients with comorbidities (64%), Frail (60%). Fit vs. frail + patients with comorbidities (p = 0.0408)

37 months. Fit (34%), patients with comorbidities (9.5%), frail (7.1%). Fit vs. frail + patients with comorbidities (p = 0.0044)

5 y EFS: fit (18.9%) patients with comorbidities (9.5%), frail (7.1%)

Early toxic deaths: fit (1.9%), patients with comorbidities (9.2%), frail (6.7%). Fit vs. frail + patients with comorbidities (p < 0.05

Hematological grade
34 toxicity: fit (7%),
patients with comorbidi-
ties (0%), frail (7%). Fit vs. patients with comorbidities + frail (p > 0.05)

Non-CGA-modulated studies

Tanaka et al. (2022)

CHOP-like (R-CHOP, R-CHOP + RTx; R-THPCOP; R-EPOCH; R-ECOP; R-CHOEP, CHOP) = 72 (92.3); low toxicity regimen (R-mini-CHP, = 6 (7.7); R-oral sobuzoxane and etoposide)

Dependent (70.7%); independent (78.4%)

4-year survival rate: independent (72.7%); dependent (56.9%).

Missing

Missing

Non-hematological toxicity: dependent (53.7%), independent (16.2%);

Zhang et al. (2022)

Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy

ORR, CR, and PR rates in the fit group were 88.2%, 58.8%, and 29.4%, respectively, while the ORR, CR, and PR rates in the unfit/frail group were 64.3%, 42.9%, and 21.4%, respectively

Median OS in the fit group (not reached) was better

The fit group had a higher median PFS rate than the unfit/frail group (11.4 months vs. 7.0 months; p = 0.037)

Missing

Hematological grade 34 toxicity: fit (23.5%), unfit/frail (50%)

Merli et al. (2021)

Full dose: R-CHOP, R-COMP, R-VNCOPB, R-DAEPOCH, R-CNOP, R-CEOP Reduced dose: R-mini-CHOP and similar Palliative therapy: R-Bendamustine, R-CVP, R-other (without anthracycline), rituximab only RT, cyclophosphamide, surgery, etoposide, prednisone, metronomic chemotherapy

NR

3 years: fit (87%), unfit (69%), frail (42%) (p < 0.001)

NR

NR

NR

Isaksen et al. (2021)

Treatment intensity was divided into 4 categories: full-dose R-CHOP, attenuated R-CHOP, anthracycline-free regimen, and no chemotherapy

Missing

2 years: fit (82%); unfit (47%); frail (14%); p < 0.001).

Missing

Missing

NR

Ong et al. (2019)

Fit: R-CHOP (55/57), R-CHEP (1/57), R-PACEBOM (1/57), unfit: R-CHOP (16/29), R-miniCHOP (8/20), R-CEOP (3/29), R-CHEP (1/57), frail: R-CHOP (34/52), R-miniCHOP (11/52), R-CEOP (6/52), R-CNOP (1/52)

Missing

2 years: fit (90%), unfit (71%), frail (56%). 3-year: fit (82%), unfit (60%), frail (53%)

PFS: 2-year fit (79%); unfit (64%), frail (65%). 3-year fit (66%), unfit (58%), frail (46%)

Fit (4%), unfit (10%), frail (10%)

Any grade3 toxicity:
fit = 72%, unfit = 62%, frail = 79%

Tucci et al. (2015)

Unfit and frail: full-dose therapy (CHOP or CHOP-like regimens with rituximab). Remaining patients received palliation [low-dose chemotherapy without anthracyclines, and prednisone (COP), low-dose COP], rituximab as a single agent, corticosteroids alone, oral mono chemotherapy or anthracycline-based cycles at a relative dose intensity less than 70%)

ORR, overall response rate (complete remission + partial remission): curative unfit = 14 (82%), frail 13 (72%), palliative: unfit = 7 (64%), frail = 25 (52%)

2 years: fit (84%), non-fit (frail + unfit) (47%) p < 0.0001

Missing

Missing

Nonhematological toxicity of grade 34: curative or palliative intent (45% vs. 38%; p = 0.3)

Marchesi et al. (2013)

Curative anthracycline-based treatment, Full-intensity R-CHOP, attenuated R-CHOP, conservative without anthracyclines (R-CVP)

Irrespective of the type of treatment, the overall response (OR), the complete response (CR), and the failure rates were 80.5%, 55.2%, and 19.5%, respectively

Irrespective of the type of treatment, “fit” and “intermediate” patients had similar outcomes, whereas “frail” patients showed a significantly worse 2-year OS rate than the other two patient categories (p < 0.001)

2-year OS and PFS rates were 39.7%

Missing

Curative vs. conservative treatments and the CGA stratification did not significantly affect the occurrence of grades 34 toxicities and toxic death incidence

In five-eighths of CGA-modulated treatment studies vs. three-eighths of non-CGA-modulated treatment studies, two-year OS of frail/unfit patients was 52% (95% CI 3866) and 27% (95% CI 1936) (p = 0.003), respectively (Fig. 2). A meta-analysis of three-year or five-year OS was not performed because there were not enough studies reporting it (minimum 2 studies).

Figure 2. Forest plot of frequencies of two-year overall survival (OS) of frail/unfit patients; A. OS2: comprehensive geriatric
assessment (CGA)-modulated studies; B. OS2: Non CGA-modulated studies; CI confidence interval

In six-ninths of CGA-modulated treatment studies vs. three-ninths of non-modulated treatment stu- dies, the CR of frail/unfit patients was 34% (95% CI 2346) and 28% (95% CI 1938) (p = 0.436), respectively (Fig. 3).

Figure 3. Forest plot of frequencies of complete response (CR) of frail/unfit patients; A. CR: comprehensive geriatric assessment (CGA)-modulated studies; B. CR: Non CGA-modulated studies; CI confidence interval

In four-sixths of CGA-modulated treatment studies with vs. two-sixths of non-modulated treatment studies, grade 34 hematological toxicity in frail/unfit patients was 26% (95% CI 555%) and 36% (95% CI 1363%) (p = 0.583), respectively (Fig. 4). While in two-fourths of CGA-modulated treatment studies vs. two-fourths of non-modulated treatment studies, grade 34 non-hematological toxicity in frail/unfit patients was 22% (95% CI 1136%) and 31% (95% CI 2537%) (p = 0.106), respectively (Fig. 5).

Figure 4. Forest plot of frequencies of grade 34 hematological toxicity in frail/unfit patients; A. Grade 34 hematologic toxicity in
frail/unfit patients [comprehensive geriatric assessment (CGA)-modulated studies]; B. Grade 34 hematologic toxicity in frail/unfit patients (Non CGA-modulated studies); CI confidence interval
Figure 5. Forest plot of frequencies of grade 34 non-hematological toxicity in frail/unfit patients; A. Grade 34 hematologic toxicity in frail/unfit patients [comprehensive geriatric assessment (CGA)-modulated studies]; B. Grade 34 hematologic toxicity in frail/unfit patients (non CGA-modulated studies); CI confidence interval

Discussion

We performed a metanalysis to compare the outcomes of non-CGA-modulated versus CGA-modulated studies in the treatment of frail/unfit older adults with DLBCL, in terms of CR, incidence of grade3 toxicity, and 2-year OS. Although the proportion of frail patients was lower in non-CGA-modulated studies and the studies had no significant differences in CR or grade 34 hematological/non-hematological toxicity, CGA-modulated studies reported higher two-year OS.

Two systematic studies with similar findings have previously been published, with studies covering the period up to 2016 [32] and 2020 [33]. Regarding the usefulness of CGA as a guide for selecting a therapeutic scheme in older DLBCL patients, there are currently two approaches. The first supports the performance of CGA as a guide in the selection of a therapeutic scheme based on risk stratification [34]. The other approach, based on a 2019 consensus, does not recommend using CGA in determining the chemotherapy regimen for older DLBCL patients. However, it concedes that CGA is useful in identifying issues that may have been overlooked and clarifies that using CGA is not ruled out in cancer patients [35].

There may be mechanisms by which categorization of patients with CGA could improve outcomes, especially in frail DLBCL patients. This strategy could reduce overtreatment in frail and undertreatment in fit patients. Frail patients have been reported to have high treatment-related mortality, especially if treated with full-dose regimens [19, 29, 36]. Frail patients have high rates of treatment discontinuation due to adverse reactions, which leads to disease progression that affects their survival, and the low tolerance to chemotherapy can be partly explained by other comorbidities [29]. The severity of these comorbidities is detected during a CGA, in which instruments such as the Cumulative Illness Rating Scale for Geriatrics (CIRS-G) can identify frailty when grade 34 comorbidities are present [37]. Modifying the dose of chemotherapy (R-CHOP) has been shown to decrease adverse reactions to chemotherapy in frail patients, without impairing the efficacy of treatment [18, 30]. In this regard, it has been postulated that the explanation for the reduced doses of anthracycline in frail patients having the same therapeutic results is that the half-life of this medication is prolonged due to the aging process and patients’ comorbidities [12, 38, 39].

Comprehensive geriatric assessment is potentially one of the strategies to predict chemotherapy tolerability, that is, it could have prognostic capacity with regard to the severity of adverse reactions associated with chemotherapy. In our study, no significant differences were found in grade3 hematological and non-hematological toxicity. The latter may be due to only 2 studies on each side of the comparison. Regarding instruments to predict adverse reactions in DLBCL patients, two strategies have been described, among which are the Elderly Prognostic Index (EPI) [22] and the Norwegian score [31]. However, it should be noted that the last two proposals contain data from CGA (e.g. activities of daily living and CIRS-G).

This study has some limitations. For example, the frail/unfit were compared as if they were a single group because most of the studies reported their data in this way. The analysis was not performed only with frail patients due to a small number of studies with such data. For the same reason, the meta-analysis was performed only with two-year OS because few studies reported data for three or five-year OS. Similarly, only a few studies reported the frequency of CR and grade 34 hematological and non-hematological toxicity. Carrying out a joint analysis of CGA as if it were a standard or homogeneous instrument might also be debatable, given that the different studies used different models for the CGA (sCGA, full CGA, and the phenotype model), which use different criteria (Tab. S2 in supplementary file). Another limitation of this study is that it only evaluated the usefulness of CGA in the reduction of the incidence of grade3 toxicity and not in relation to specific types of adverse drug reactions (ADR). It is known that toxicities for chemo or non-chemo protocols may be different; for example, the ADR called “immune effector cell-associated neurotoxicity syndrome (ICANS)” occurs only with chimeric antigen receptor (CAR) T-cell therapy [40].

Conclusions

In conclusion, our metanalysis suggests that CGA could serve as a guide for the treatment plan in older DLBCL patients and lead to better patient survival. Randomized clinical trials are necessary to confirm these findings as well as the standardization and homogenization of the instruments used in CGA.

Article Information and Declarations

Author contributions

T.J.O.: concept and design, acquisition, analysis, and interpretation of the data, drafting of the manuscript, critical revision of the manuscript; X.V.: analysis, and interpretation of the data, critical revision of the manuscript; B.E.B.: acquisition, analysis, and interpretation of the
data, drafting of the manuscript, critical revision
of the manuscript; R.R.-O.: acquisition, analysis, and interpretation of the data, drafting of the manuscript, critical revision of the manuscript, supervision.

Funding

None.

Acknowledgments

None.

Conflict of interest

None.

Supplementary material

Tables S1 and S2.

References

  1. Sun J, Yang Q, Lu Z, et al. Distribution of Lymphoid Neoplasms in China. Am J Clin Pathol. 2012; 138(3): 429434, doi: 10.1309/ajcp7yltqpusdq5c.
  2. Fields PA, Linch DC. Treatment of the elderly patient with diffuse large B cell lymphoma. Br J Haematol. 2012; 157(2): 159170, doi: 10.1111/j.1365-2141.2011.09011.x, indexed in Pubmed: .
  3. Ruppert AS, Dixon JG, Salles G, et al. International prognostic indices in diffuse large B-cell lymphoma: a comparison of IPI, R-IPI, and NCCN-IPI. Blood. 2020; 135(23): 20412048, doi: /blood.2019002729, indexed in Pubmed: 32232482.
  4. Zhou Z, Sehn LH, Rademaker AW, et al. An enhanced International Prognostic Index (NCCN-IPI) for patients with diffuse large B-cell lymphoma treated in the rituximab era. Blood. 2014; 123(6): 837842, doi: /blood-2013-09-524108.
  5. Melchardt T, Troppan K, Weiss L, et al. A modified scoring of the NCCN-IPI is more accurate in the elderly and is improved by albumin and β2 -microglobulin. Br J Haematol. 2015; 168(2): 239245, doi: /bjh.13116, indexed in Pubmed: 25236324.
  6. Pfreundschuh M. How I treat elderly patients with diffuse large B-cell lymphoma. Blood. 2010; 116(24): 51035110, doi: /blood-2010-07-259333, indexed in Pubmed: 20805363.
  7. Romero-Ortuno R, O’Shea D. Fitness and frailty: opposite ends of a challenging continuum! Will the end of age discrimination make frailty assessments an imperative? Age Ageing. 2013; 42(3): 279280, doi: /ageing/afs189, indexed in Pubmed: 23348509.
  8. Handforth C, Clegg A, Young C, et al. The prevalence and outcomes of frailty in older cancer patients: a systematic review. Ann Oncol. 2015; 26(6): 10911101, doi: /annonc/mdu540, indexed in Pubmed: 25403592.
  9. Ellis G, Gardner M, Tsiachristas A, et al. Comprehensive geriatric assessment for older adults admitted to hospital. Cochrane Database Syst Rev. 2017; 9(9): CD006211, doi: /14651858.CD006211.pub3, indexed in Pubmed: 28898390.
  10. Hanna K, Ditillo M, Joseph B. The role of frailty and preha- bilitation in surgery. Curr Opin Crit Care. 2019; 25(6): 717722, doi: /MCC.0000000000000669, indexed in Pubmed: 31689246.
  11. Overcash J, Ford N, Kress E, et al. Comprehensive Geriatric Assessment as a Versatile Tool to Enhance the Care of the Older Person Diagnosed with Cancer. Geriatrics (Basel). 2019; 4(2), doi: /geriatrics4020039, indexed in Pubmed: 31238518.
  12. Soverini G, Tucci A. Clinical geriatric assessment in older patients with lymphoma: a narrative review. Ann Lymphoma. 2022; 6: 1111, doi: /aol-22-6.
  13. Moher D, Liberati A, Tetzlaff J, et al. PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009; 339: b2535, doi: /bmj.b2535, indexed in Pubmed: 19622551.
  14. National Cancer Institute. Common Terminology Criteria for Adverse Events (CTCAE). (2023). https:/ctep.cancer.gov/protocoldevelopment/electronic_applications/ctc.htm.
  15. von Elm E, Altman DG, Egger M, et al. STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg. 2014; 12(12): 14951499, doi: /j.ijsu.2014.07.013, indexed in Pubmed: 25046131.
  16. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986; 7(3): 177188, doi: /0197-2456(86)90046-2, indexed in Pubmed: 3802833.
  17. Spina M, Balzarotti M, Uziel L, et al. Modulated chemotherapy according to modified comprehensive geriatric assessment in 100 consecutive elderly patients with diffuse large B-cell lymphoma. Oncologist. 2012; 17(6): 838846, doi: /theoncologist.2011-0417, indexed in Pubmed: 22610154.
  18. Olivieri A, Gini G, Bocci C, et al. Tailored therapy in an unselected population of 91 elderly patients with DLBCL prospectively evaluated using a simplified CGA. Oncologist. 2012; 17(5): 663672, doi: /theoncologist.2011-0355, indexed in Pubmed: 22531362.
  19. Merli F, Luminari S, Rossi G, et al. Fondazione Italiana Linfomi. Outcome of frail elderly patients with diffuse large B-cell lymphoma prospectively identified by Comprehensive Geriatric Assessment: results from a study of the Fondazione Italiana Linfomi. Leuk Lymphoma. 2014; 55(1): 3843, doi: /10428194.2013.788176, indexed in Pubmed: 23517562.
  20. Storti S, Spina M, Pesce EA, et al. Rituximab plus bendamustine as front-line treatment in frail elderly (>70 years) patients with diffuse large B-cell non-Hodgkin lymphoma: a phase II multicenter study of the . Haematologica. 2018; 103(8): 13451350, doi: /haematol.2017.186569, indexed in Pubmed: 29748444.
  21. Bocci G, Pelliccia S, Orlandi P, et al. Remarkable Remission Rate and Long-Term Efficacy of Upfront Metronomic Chemotherapy in Elderly and Frail Patients, with Diffuse Large B-Cell Lymphoma. J Clin Med. 2022; 11(23), doi: /jcm11237162, indexed in Pubmed: 36498736.
  22. Merli F, Luminari S, Tucci A, et al. Simplified Geriatric Assessment in Older Patients With Diffuse Large B-Cell Lymphoma: The Prospective Elderly Project of the Fondazione Italiana Linfomi. J Clin Oncol. 2021; 39(11): 12141222, doi: /JCO.20.02465, indexed in Pubmed: 33577377.
  23. Marchesi F, Cenfra N, Altomare L, et al. A retrospective study on 73 elderly patients (≥75years) with aggressive B-cell non Hodgkin lymphoma: clinical significance of treatment intensity and comprehensive geriatric assessment. J Geriatr Oncol. 2013; 4(3): 242248, doi: /j.jgo.2013.04.003, indexed in Pubmed: 24070462.
  24. Tucci A, Martelli M, Rigacci L, et al. Italian Lymphoma Foundation (FIL). Comprehensive geriatric assessment is an essential tool to support treatment decisions in elderly patients with diffuse large B-cell lymphoma: a prospective multicenter evaluation in 173 patients by the Lymphoma Italian Foundation (FIL). Leuk Lymphoma. 2015; 56(4): 921926, doi: /10428194.2014.953142, indexed in Pubmed: 25110825.
  25. Bai JF, Han HX, Feng Ru, et al. Comprehensive Geriatric Assessment (CGA): A Simple Tool for Guiding the Treatment of Older Adults with Diffuse Large B-Cell Lymphoma in China. Oncologist. 2020; 25(8): e1202e1208, doi: /theoncologist.2019-0738, indexed in Pubmed: 32436258.
  26. Xu PP, Shi ZY, Qian Y, et al. Ibrutinib, rituximab, and lenalidomide in unfit or frail patients aged 75 years or older with de novo diffuse large B-cell lymphoma: a phase 2, single-arm study. Lancet Heal Longev. 2022; 3(7): e481e490, doi: /S2666-7568(22)00123-4, indexed in Pubmed: 36102758.
  27. Zhang H, Liu M, Li Q, et al. Evaluation of the safety and efficacy of humanized anti-CD19 chimeric antigen receptor T-cell therapy in older patients with relapsed/refractory diffuse large B-cell lymphoma based on the comprehensive geriatric assessment system. Leuk Lymphoma. 2022; 63(2): 353361, doi: /10428194.2021.1986216, indexed in Pubmed: 34587859.
  28. Ong DM, Ashby M, Grigg A, et al. Comprehensive geriatric assessment is useful in an elderly Australian population with diffuse large B-cell lymphoma receiving rituximab-chemotherapy combinations. Br J Haematol. 2019; 187(1): 7381, doi: /bjh.16049, indexed in Pubmed: 31206608.
  29. Tanaka T, Sakai R, Choi I, et al. Comprehensive geriatric assessment as a useful tool in predicting adverse events in elderly patients with diffuse large B-cell lymphoma. Sci Rep. 2022; 12(1): 3124, doi: /s41598-022-07164-w, indexed in Pubmed: 35210509.
  30. Lastra-German IK, Navarrete-Reyes AP, Mejía-Domínguez NR, et al. Adjusted Chemotherapy According to Frailty Status in Elderly Patients With Diffuse Large B-Cell Lymphoma: Experience From a Single Referral Center in Mexico City. Clin Lymphoma Myeloma Leuk. 2019; 19(2): e98e9e106, doi: /j.clml.2018.11.013, indexed in Pubmed: 30545670.
  31. Isaksen KT, Mastroianni MA, Rinde M, et al. A simplified frailty score predicts survival and can aid treatment-intensity decisions in older patients with DLBCL. Blood Adv. 2021; 5(22): 47714782, doi: /bloodadvances.2021004777, indexed in Pubmed: 34543384.
  32. Lin RJ, Behera M, Diefenbach CS, et al. Role of anthracycline and comprehensive geriatric assessment for elderly patients with diffuse large B-cell lymphoma. Blood. 2017; 130(20): 21802185, doi: /blood-2017-05-736975.
  33. Tavares A, Moreira I. Diffuse large B-cell lymphoma in very elderly patients: Towards best tailored treatment - A systematic review. Crit Rev Oncol Hematol. 2021; 160: 103294, doi: /j.critrevonc.2021.103294, indexed in Pubmed: 33675907.
  34. Buske C, Hutchings M, Ladetto M, et al. ESMO Lymphoma Consensus Conference Panel Members. ESMO Consensus Conference on malignant lymphoma: general perspectives and recommendations for the clinical management of the elderly patient with malignant lymphoma. Ann Oncol. 2018; 29(3): 544562, doi: /annonc/mdx413, indexed in Pubmed: 29194473.
  35. JSMOJSCO. Chemotherapy and other drug therapies for older patients with cancer: JSMO-. JSCO clinical practice guidelines. 2019. https:/www.jsmo.or.jp/about/doc/guideline01_03.pdf.
  36. Tucci A, Ferrari S, Bottelli C, et al. A comprehensive geriatric assessment is more effective than clinical judgment to identify elderly diffuse large cell lymphoma patients who benefit from aggressive therapy. Cancer. 2009; 115(19): 45474553, doi: /cncr.24490, indexed in Pubmed: 19562776.
  37. Miller MD, Paradis CF, Houck PR, et al. Rating chronic medical illness burden in geropsychiatric practice and research: application of the Cumulative Illness Rating Scale. Psychiatry Res. 1992; 41(3): 237–248, doi: /0165-1781(92)90005-n, indexed in Pubmed: 1594710.
  38. Carson KR, Riedell P, Lynch R, et al. Comparative effectiveness of anthracycline-containing chemotherapy in United States veterans age 80 and older with diffuse large B-cell lymphoma. J Geriatr Oncol. 2015; 6(3): 211218, doi: /j.jgo.2015.01.003, indexed in Pubmed: 25614297.
  39. Peyrade F, Jardin F, Thieblemont C, et al. Groupe d’Etude des Lymphomes de l’Adulte (GELA) investigators. Attenuated immunochemotherapy regimen (R-miniCHOP) in elderly patients older than 80 years with diffuse large B-cell lymphoma: a multicentre, single-arm, phase 2 trial. Lancet Oncol. 2011; 12(5): 460468, doi: /S1470-2045(11)70069-9, indexed in Pubmed: 21482186.
  40. Grant SJ, Grimshaw AA, Silberstein J, et al. Clinical Presentation, Risk Factors, and Outcomes of Immune Effector Cell-Associated Neurotoxicity Syndrome Following Chimeric Antigen Receptor T Cell Therapy: A Systematic Review. Transplant Cell Ther. 2022; 28(6): 294302, doi: /j.jtct.2022.03.006, indexed in Pubmed: 35288347.
Table S1. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) checklist (from [13])

Section/topic

#

Checklist item

Reported on page #

Title

Title

1

Identify the report as a systematic review, meta-analysis, or both

1

Abstract

Structured summary

2

Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number

3

Introduction

Rationale

3

Describe the rationale for the review in the context of what is already known

4

Objectives

4

Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS)

4

Methods

Protocol and registration

5

Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number

Eligibility criteria

6

Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale

5

Information sources

7

Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched

Search

8

Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated

5

Study selection

9

State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis)

5

Data collection process

10

Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators

5

Data items

11

List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made

5

Risk of bias in individual studies

12

Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis

5

Summary measures

13

State the principal summary measures (e.g., risk ratio, difference in means).

5

Synthesis of results

14

Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I2) for each meta-analysis

Risk of bias across studies

15

Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies)

Additional analyses

16

Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified

Results

Study selection

17

Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram

6

Study characteristics

18

For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations

6

Risk of bias within studies

19

Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12)

6

Results of individual studies

20

For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot

6

Synthesis of results

21

Present results of each meta-analysis done, including confidence intervals and measures of consistency

6

Risk of bias across studies

22

Present results of any assessment of risk of bias across studies (see item 15).

6

Additional analysis

23

Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression (see item 16)]

Discussion

Summary of evidence

24

Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers)

7

Limitations

25

Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias)

8

Conclusions

26

Provide a general interpretation of the results in the context of other evidence, and implications for future research

8

Funding

Funding

27

Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review

1

Table S2. Frailty classification in older patients with diffuse large B-cell lymphoma

Study

Operational definition

Frail

Unfit

Fit

CGA-modulated studies

Xu et al (2022)

Frail: ADL < 5; IADL < 6; CIRS-G: 1 grade 34 comorbidities or > 8 comorbidities grade 2 score; age80 o morbidities), age80 unfit

Unfit: ADL6-5; IADL67; CIRS-G: no comorbidities score 34 and 58 comorbidities score 2, age80 fit

Fit: ADL6-6; IADL = 8; CIRS-G: no comorbidities score 34 and < 5 comorbidities score 2

Bocci et al. (2022)

Frail: age80 years and CIRS-G:1 score = 34;5 score 5 = 2; ADL < 6; and IADL < 8 scores

Unfit: < 80: CIRS-G:1 score = 34; > 8 score = 2; ADL < 5; and IADL < 6; unfit:80: CIRS-G:0 score = 34; < score = 2; ADL = 6; and IADL = 8

Bai et al. (2020)

Frail: ADL < 5 or IADL < 6; or MCIRS-G:1 comorbidity score 34 (or > 8 comorbidity score 2) or age80 yr unfit

Unfit: ADL = 5 or IADL = 67 or MCIRS-G = no comorbidity score 34 (and 58 comorbidity score 2) or; age80 yr fit

Fit: ADL = 6 and IADL = 8 and MCIRS no comorbidity score 34 (and < 5 comorbidity score 2); and; age = And < 80 yr

Storti et al. (2018)

Frail: inpatients aged between 70 and 80 years, ADL < 4 or IADL < 5 or 1 grade 3 comorbidity or > 8 grade 2 comorbidities (CIRS-G) were required; in patients older than 80 years, ADL > 5 or IADL > 6 or 58 grade 2 comorbidities were required

Lastra-German et al. (2018)

3 points: frail 1. Unintentional loss of5 kg during the past year 2. Physical exhaustion: The previous week… a) “Did you feel that everything required a lot of effort?”; b) „Did you feel that you could not go on?”; “Moderate amount” or “most of the time” in any circumstance scores as positive; 3. Low physical activity: Lowest quintile adjusted for gender; 4. Slowness: 4-meter gait speed below the lowest quintile adjusted for height*; 5. Weakness: grip strength below the lowest quintile adjusted for BMI

12 points: unfit

0 points: fit

Merli et al. (2013)

Frail:80 years; or frail: < 80 years who were not fit according to one or more of the previous features were also considered as frail

Missing

Fit: < 80 years and had an ADL = 6, < 3 grade 3 CIRS-G comorbidities and no grade 4 comorbidities (hematological comorbidities were not investigated), and none of the criteria defining the presence of geriatric syndrome

Spina et al. (2012)

Frail: ADL < 5, or IADL < 5. CIRS-G:1 grade 3 comorbidities (or > 5 grade 2 comorbidities)

Unfit: an ADL = 5, and/or an IADL = 5 or 6; CIRS-G: no grade 3 comorbidities (or 35 grade 2 comorbidities)

Fit: ADL = 6, and/or an IADL = 7 or 8; CIRS-G: no grade 3 comorbidities (or < 3 grade 2 comorbidities)

Olivieri et al. (2012)

Frail: age85 years and dependence1 ADLs and geriatric syndromes:1. Frail: CIRS-G score3

Patients with comorbidities: CIRS-G score 02

Fit (no frail, no patientes with comorbidities)

Tanaka et al. (2022)

Dependent:1 problems in 6 CGA domains; a) ADL Barthel Index < 100; b) IADL (Lawton and Brody) < 5; c) Psychological status GDS-15 > 10; d) Cognitive function Hasegawa’s dementia scale (HDS-R) 20; e) Nutritional status MNA < 17; g) Comorbidities Charlson comorbidity index5 MNA < 17; comorbidities Charlson comorbidity index5

Missing

Independent = remaining cases were definedas „independent”

Zhang et al. (2022)

Frail: > 80 y or80 y with CIRS-G: any grade 3 or 4 comorbidities or > 8 grade 2 comorbidities or with higher scores on the ADLs/IADLs scales

Unfit80y with an ADL = 5, an IADL = 67, CIRS-G: no grade 3 or 4 comorbidities, and 58 grade 2 comorbidities

Fit80 y with normal ADLs and IADLs scores, CIRS-G: no grade 3 or 4 comorbidities, and < 5 grade 2 comorbidities

Merli et al. (2021)

Frail: age80 years and CIRS-G:1 score = 34;5 score 5 = 2; ADL < 6; and IADL < 8 scores

Unfit: < 80: CIRS-G:1 score = 34; > 8 score = 2;ADL < 5; and IADL < 6 unfit:80: CIRS-G:0 score = 34; < score = 2; AD = 6; and IADL = 8

Fit:80: CIRS-G:0 score = 34;8 score = 0; ADL5; and IADL6

Isaksen et al. (2021)

Frail: Katz Activities of Daily Living (ADL): independent = 1, dependent = 2; Charlson Comorbidity Index (CCI): score 01 = 1; score 2 = 1.5; score3 = 2; Geriatric Nutritional Risk Index (GNRI): absent/low = 1; moderate = 2; severe = 2.5; age: < 85 = 1;85 = 2; total score: multiply obtained scores (rank: 120) (example: ADL = 2, CCI = 2; GNRI = 2; age: 2. Total Score = 2 × 2 × 2 × 2 = 16). Frail: total score > 3

Unfit: score: 1.53

Fit score = 1

Ong et al. (2019)

Frail: those not meeting CGA-fit or unfit criteria were classified CGA-frail

Unfit: aged80 years, with ADL = 5, IADL = 7, no CIRS-G grade 34 comorbidities and up to 58 grade 2 comorbidities

Fit: aged < 80 years, with no limitations in ADL (score 6/6) and IADL (score 8/8), CIRS-G no severe comorbidities grade 34/4 (excluding haemato­logical comorbidities) and < 5 grade 24 comorbidities

Tucci et al. (2015)

Frail: ADL4, IADL5, CIRS-G1 comorbidity score 34 or > 8 comorbidity score 2, age80

Unfit: ADL 5, IADL 76, CIRS-G no comorbidity score 34 and 58 score 2, age80

Fit: ADL 6, IAL 8, CIRS-G no comorbidity score 34 and < 5 score 2

Marchesi et al. (2013)

Frail (CGA 3):1 of the following parameters: age > 85 years, presence of a geriatric syndrome, ADL score < 6) and3 moderate morbidities or one or more severe morbidities

Intermediate (CGA 2) < 85 years old, ADL = 6; and at least one moderate morbidity but no geriatric syndromes

Fit: < 85 years, ADL = 6 and no moderate morbidities and geriatric syndromes