Frailty assessment tools and geriatric assessment in older patients with hepatobiliary and pancreatic malignancies

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University of Groningen

Frailty assessment tools and geriatric assessment in older patients with hepatobiliary and

pancreatic malignancies

Rostoft, Siri; van Leeuwen, Barbara

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European Journal of Surgical Oncology

DOI:

10.1016/j.ejso.2020.08.024

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Publication date:

2021

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Rostoft, S., & van Leeuwen, B. (2021). Frailty assessment tools and geriatric assessment in older patients

with hepatobiliary and pancreatic malignancies. European Journal of Surgical Oncology, 47(3 Part A),

514-518. https://doi.org/10.1016/j.ejso.2020.08.024

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Consensus Statement

Frailty assessment tools and geriatric assessment in older patients

with hepatobiliary and pancreatic malignancies

Siri Rostoft

a,b,*

, Barbara van Leeuwen

c

a_{Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway} b_{Institute of Clinical Medicine, University of Oslo, Oslo, Norway}

c_{Department of Surgical Oncology, University Medical Center Groningen, Groningen University, Groningen, the Netherlands}

a r t i c l e i n f o

Article history:

Accepted 22 August 2020 Available online 25 August 2020 Keywords: Frailty Geriatric assessment Preoperative assessment Assessment tools Older adults Hepatobiliary disorders Cancer

a b s t r a c t

Background: The majority of patients with hepatobiliary and pancreatic (HBP) malignancies are older than 65 years. Due to the heterogeneity of this older population, decisions regarding surgical treatment cannot rely solely on treatment guidelines, but have to take into account patient frailty, geriatric im-pairments and resilience as well as patient preferences. In the few studies of older patients with HBP malignancies that have included a preoperative geriatric assessment (GA), frailty and elements from the GA such as reduced functional status have emerged as powerful predictors of postoperative morbidity and mortality, length of stay, type of treatment received and survival. A GA is a systematic evaluation of functional status, comorbidities, polypharmacy, cognition, nutritional status, emotional status, and social support.

Materials and methods: A Pubmed search identifying clinical studies investigating the association be-tween frailty, GA and outcomes in patients with HBP malignancies.

Results: A total of 20 studies were included in this review. For HBP malignancies, the evidence linking frailty and GA variables to negative outcomes is limited, but generally shows that frailty, functional dependency, comorbidity, and sarcopenia predict postoperative complications and survival.

Conclusion: Although scarcely investigated, frailty and elements from a GA seem to be associated with negative short- and long-term treatment outcomes in older patients with HBP malignancies. Future studies should investigate the impact of geriatric interventions and prehabilitation on outcomes.

Introduction

The majority of patients with hepatobiliary and pancreatic (HBP) malignancies are older than 65 years. With increasing age, the heterogeneity in the population becomes more evident, and patients may accumulate comorbidity and frailty in addition to their cancer disease. Frailty is defined as a multisystem reduction in reserve capacity, and a patient who is frail has shorter life expec-tancy and higher risk of complications after surgery than afit pa-tient of the same age [1,2]. Many studies have shown that even older patients can tolerate extensive surgery for HBP cancer, but the patients included in such studies are often highly selected. Benefits of surgery seen in non-frail older patients may not be evident in

frail patients, and the decision-making needs to incorporate ele-ments of a geriatric assessment (GA) to evaluate frailty. A GA is a structured evaluation of areas where older patients often present with impairments, and includes functional and cognitive status, mobility, sarcopenia, comorbidities, polypharmacy, emotional sta-tus, nutritional stasta-tus, and social network. Based on this assessment the degree of frailty can be estimated, impairments can be targeted (prehabilitation), and shared decision-making can be informed [3]. Theﬁnal decision regarding surgical treatment will depend on the individual patient’s goals, priorities and preferences; and expected

risks and beneﬁts from treatment are highly dependent on the

patient’s vulnerabilities and resilience which becomes clearer during the GA. In this review we aim to discuss the literature regarding frailty screening tools and GA in older patients under-going HBP surgery.

* Corresponding author. Department of Geriatric Medicine, Oslo University Hospital, Pb 4956 Nydalen, 0424, Oslo, Norway.

E-mail address:srostoft@gmail.com(S. Rostoft).

Contents lists available atScienceDirect

European Journal of Surgical Oncology

j o u rn a l h o m e p a g e : w w w . e js o . c o m

https://doi.org/10.1016/j.ejso.2020.08.024

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Methods

The aim was to identify clinical studies that investigated the association between frailty or GA and outcomes in patients with liver cancer, biliary cancer, and pancreatic cancer. The following searches were performed on July 15, 2020 in PubMed: (geriatric assessment AND (biliary cancer OR liver cancer OR pancreatic cancer) and frailty AND (biliary cancer OR liver cancer OR pancre-atic cancer)). Only papers published in the last 10 years and in English were included. Studies were not eligible if the cohort consisted of non-cancer patients. Reviews and studies that did not include frailty or GA data were excluded.

Results

The searches yielded a total of 181 references; 86 for GA and 95 for frailty. A total of 161 studies were excluded due to reviews without original data (n _{¼ 3), not including frailty or geriatric} assessment data (n¼ 122), not relevant due to mix of cancer types (GI and non-GI) or non-cancer data (n¼ 26). A total of 20 studies were original studies including data on frailty, GA and HBP cancer. The results are summarized inTable 1andTable 2.

Few studies have looked at the predictive ability of GA in older patients undergoing HBP surgery for cancer. Most studies divide their patients in an older versus younger cohort andﬁnd that age is a predictor of complications, but this may be less interesting in clinical practice. Firstly, because age is a non-modiﬁable risk factor, and secondly because frailty and GA provides more information than chronological age alone. The largest study was retrospective and published by De la Fuente and colleagues [4]. In a cohort of 6293 patients who underwent pancreaticoduodenectomy (PD) included in the National Surgical Quality Improvement Program

(NSQIP) database for 2005e2009, they looked at 30-day

post-operative mortality, major complication rate and overall compli-cation rate and compared younger patients to the 9.4% of patients who were older than 79 years. Age was an independent predictor of

all outcomes, but the multivariate analysis showed that decreased functional status had the greatest predictive value for postoperative

mortality (odds ratio (OR) 2.80, 95% CI 2.73e4.51) and major

complication rate (OR 2.16, 95% CI 1.60e2.90). Decreased functional status was measured by ability to perform activities of daily living (ADLs) during the 30 days prior to surgery. Patients who were partially or totally dependent were classified as having a reduced functional status. Two studies looked at the ability of the Fried’s criteria for frailty (low grip strength, slow walking speed, self-reported exhaustion, weight loss and low activity [11]) to predict post-operative complications after PD. In the study by Dale and colleagues, 76 patients were included [5], while Benjamin and colleagues included 134 patients of whom 64 had GA data available [6]. Both studies found self-reported exhaustion to be an inde-pendent predictor of post-operative complications. The OR of major complications was 4.06 in the study by Dale, and in that study age, body mass index (BMI), ASA score, mobility measured by the short physical performance battery (SPPB) and comorbidities did not predict complications. Exhaustion did not predict discharge to a rehabilitation facility or readmission. In the study by Benjamin, which was mainly a study of imaging analysis in patients under-going pancreatic surgery, self-reported exhaustion predicted serious complications with an OR of 3.16 (95% CI 1.08e10.1) when corrected for age, BMI, comorbidities, ASA score, and psoas Houndsfield units. Two other studies included data on frailty and physical function and outcomes after pancreatic resection in older adults [7,8]. In a study by Ngo-Huang frailty was a predictor of survival in patients with pancreatic cancer who were treated with curative intent. Specific surgical outcomes were not investigated. In a small study by Sugimachi and colleagues about immunonutrition and physical status in older patients undergoing PD, only 37 of 92 patients had data regarding physical status. The authors conclude that physical function is often impaired, but they didn’t analyze the relation between physical function and outcomes.

We found two studies that looked at frailty, GA and hepatic resections in older patients [9,10]. In a retrospective study by

Table 1

Geriatric assessment and hepatocellular carcinoma, pancreatic cancer and hepatopancreaticobiliary surgery.

Author Year Population GA Outcomes Results

De la Fuente [4]

2011 Pancreaticoduodenectomy, divided into 79þ and younger. 6293 patients, 9.4%> 79 years

NSQIP data, including functional dependency

30-day mortality, major complication rate and overall complication rate

Reduced functional status greatest predictive value for postoperative death (OR 2.80 (2.73e4.51)) and for postoperative death and major complications (OR 2.16 (1.60e2.90))

Dale [5] 2014 Pancreaticoduodenectomy,> 64 years, 76 patients Exhaustion, SPPB<10, VES-13> 3, comorbidities Major post-operative complications, discharge to a rehab facility

Exhaustion predicted complications, SPPB predicted discharge to a rehab facility

Benjamin [6]

2017 Pancreatic surgery (n¼ 134, 63 had GA data), age 65 years

SPPB and exhaustion, grip strength

NSQIP serious complication Exhaustion predicted complications (together with BMI and body imaging) Ngo-Huang [7] 2019 Pancreatic adenocarcinoma (n¼ 142, median 65 y, 47 were surgical candidates Fried’s phenotypic frailty criteria

Survival Frailty predicted survival in patients treated with curative intent

Sugimachi [8]

2019 Pancreaticoduodenectomy (n¼ 92, 13 over age 79, 37 had evaluation of physical function

Grip strength, gait speed, 6MWT

Postoperative complications

Physical function not tested as predictor

Kaibori [9] 2015 Hepatocellular carcinoma (n¼ 71, over 70 years, retrospective)

Cognition Nutritional and functional status, comorbidities G8

Postoperarive morbidity G8<14 independently predicted postoperative complications

Tanaka [10]

2018 Hepatic resection,>64 years (217 patients, 63 classiﬁed as frail, mean age 72e75 y)

Majority HCC

Kihon Checklist, frailty>7/25

Selected complications, delirium, transfer to rehab facility, dependency

Frail patients had higher rate of events, 31.7% vs 7.8%

Abbreviations: GA; geriatric assessment; NSQIP: National Surgical Quality Improvement Program; OR: odds ratio; SPPB: short physical performance battery; VES-13: vulnerable elders survey-13; 6MWT: 6 minute walking test; G8: geriatric-8; HCC: hepatocellular carcinoma.

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Kaibori and colleagues, patients had GA at baseline. Patients were followed, and cognition, nutritional and functional status, and burden of comorbidities were reassessed at 1, 3, and 6 months postoperatively. Postoperative morbidities were recorded. In the multivariate analysis, a Geriatric-8 (G8) score of<14 was an inde-pendent predictor of complications, but the confidence interval was very wide, indicating heterogeneity in the quite small dataset of 71 patients. Tanaka and colleagues included 217 patients over 64 years who were independent before surgery. They used the Kihon checklist to define frailty. The Kihon checklist was developed in Japan, and identifies individuals 65 years at an increased risk of needing care or support in the near future [12]. It consists of 25 questions regarding ADLs, physical strength, nutrition, cognition, and mood; and a score of8 correlates with frailty. Frailty was a significant predictor of postoperative complications with an OR of 5.16 (95% CI 2.30e11.56), and except for frailty only the surgery-related factor resection of 2 sectors was retained as an indepen-dent predictor in the multivariate model.

Frailty screening tools and HBP surgery

It is in the nature of surgeons to look for quick and easy to use screening tools helping them in the decision of whether or not to

perform surgery on a patient. It is striking that in thefield of HBP surgery, more than in other types of cancer surgery, there has been a lot of interest on the predictive value of sarcopenia on post-operative outcomes, as part of or proxy for frailty screening. Several authors since 2012 have found sarcopenia to be predictive of postoperative mortality, both in thefirst 30 days following surgery, as well as up to 3 years postoperatively [13e15]. Sarcopenia is usually defined as either the total psoas area measured on CT scan or the psoas density.

The association between sarcopenia and postoperative compli-cations includingﬁstulas (a common and severe problem following PD) has also been shown [15e19]. In addition, Namm showed that following a pancreaticoduodenectomy, sarcopenic patients are more likely to be discharged to a nursing facility instead of inde-pendent living [19].

Gani [17] went on to test the predictive value of the revised Frailty Index (rFI) including ASA class, BMI, serum albumin, he-matocrit, underlying pathology, and type of liver resection. This combination of variables accurately predicted postoperative morbidity, mortality and prolonged length of hospital stay.

In a retrospective study by Buettner et al., 987 out of 1326 pa-tients underwent either pancreatic or liver surgery [20]. The objective was to identify factors predictive of postoperative

Table 2

Frailty screening tools and hepatocellular carcinoma, pancreatic cancer and hepatopancreaticobiliary surgery.

Author Year Population Screening tool Outcomes Results

Peng [13] 2012 Pancreatic resection. n¼ 557, mean age 65 y

Sarcopenia (total psoas area on CT imaging)

Survival Sarcopenia independently associated with increased risk of death at 3 y (HR¼ 1.63, P < 0.001) Buettner [20] 2016 Pancreatic, liver or colorectal

procedure. n¼ 1326 Mean age 62.5 y

Sarcopenia (psoas density on CT imaging), anemia, ECOG performance, mFI score, ASA

Survival,

complication, length of stay, ICU admittance

Sarcopenia combined with age, anemia predictive of 1 year mortality better than mFI, ASA and ECOG

Nishida [18] 2016 Pancreaticoduo-denectomy, n¼ 266, median age 69 y

arcopenia Pancreaticﬁstula Sarcopenia predictive of postoperativeﬁstula Augustin

[16]

2016 Pancreatic surgery n¼ 13,020, age 58e72 y

mFI (11 items) Postoperative

mortality and complications

Every 1-point increase in mFI increased risk of grade 4 complications (~2e6 times) and mortality (~2e10 times)

Delitto [14] 2016 Pancreatic surgery n¼ 73 Psoas index survival Psoas index predictive of survival (HR 0.021) Mogal [21] 2017 Pancreatico- duodenectomy,

n¼ 9986, mean age 65 y

mFI (11 items) Postoperative

morbidity and 30 day mortality

High mFI predictor of morbidity and mortality (OR 1.544, 1.536)

Namm [19] 2017 Pancreatico- duodenectomy, n¼ 116, mean age 65.5 y

Sarcopenia Discharge facility,

complication, LOS, recurrence, readmissions

Sarcopenia predictor of posopertive complication (OR 4.23) and discharge to SNF (OR 0.79)

Wagner [15] 2018 Pancreatic surgery, n¼ 424, median age 63 y

Skeletal muscle mass, CCI, ASA Postoperative complication, 30 day mortality

Low skeletal muscle mass associated with postoperative complications (OR 1.55)

CCI6 and low skeletal muscle mass RR 9.78 of 30 day mortality

Gani [17] 2017 Liver resection, n¼ 2714, median age 60 y

Revised frailty index: ASA class, BMI, serum albumin, hematocrit, underlying pathology, and type of liver resection

Morbidity and mortality

he rFI demonstrated good model discrimination (AUROC¼ 0.68)

Chen [22] 2018 Combined colorectal and liver resection, n¼ 1928, mean age 59 y

amFI (5 items) 30 day morbidity mFI 2 1.41-fold increased odds of overall morbidity, 2 fold increase of serious postoperative morbidity Ramanathan

[23]

2019 Major cancer surgery including liver and pancreas surgery (40%), n¼ 61,683, mean age 62.4 y

mFI, amFI, camFI Discharge location, complication LOS

The camFI performs better in predicting discharge disposition.

Tanaka [24] 2019 Hepatic resection, n¼ 347, age 65 y

Kihon checklist Postoperative loss of independence

railty, age 76 years, and open surgery were independent risk factors for postoperative loss of independence

Ishihara [25] 2020 Hepatic resection, n¼ 295, age 65y

Kihon checklist Postoperative

delirium

Total Kihon Checklist score (6 points), age (75 years), and serum albumin concentration (3.7 g/dL) were the independent risk factors for postoperative delirium

Abbreviations: y: years; HR: hazard ratio; ECOG: Eastern Cooperative Oncology Group; mFI: modified frailty index; ICU: intensive care unit; OR: odds ratio; LOS: length of stay; SNF: skilled nursing facility; CCI: Charlson comorbidity index; RR: relative risk; BMI: body mass index; AUROC: area under the receiver operating characteristic curve; amFI: abbreviated modified frailty index; camFI: cancer abbreviated modified frailty index.

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mortality and to validate the modified frailty index (mFI) in a hepatobilliary population. This mFI wasfirst described by Karam et al. in a population of vascular patients [26]. Patients are assigned 1 point if a certain comorbidity is present. These comorbidities include: diabetes; hypertension; congestive heart failure (CHF); myocardial infarction; percutaneous coronary intervention (PCI) or angina; chronic obstructive pulmonary disease (COPD); peripheral vascular disease; impaired sensorium; history of either transient ischemic attack or cerebrovascular accident (CVA); and non-independent functional status. Frailty is defined based on the to-tal scores: no frailty (mFI of 0), mFI 1 or 2 (low frailty), mFI 3 or 4 (intermediate frailty), and mFI 5 or more (frail). Although Buettner found sarcopenia combined with age and anemia to be more pre-dictive of 1 year mortality than the mFI, several authors have continued to study and adjust the mFI in search of a perfect frailty screening tool.

Augustin validated the mFI in a retrospective analysis of NSQIP, which included over 13,000 patients that had undergone pancre-atic surgery [16]. He found that every one-point increase in mFI score increased the risk of mortality 2e10 times and the risk of a grade 4 complication 2e6 times. Mogal [21] repeated these results in a largely comparable cohort.

Chen [22] recently studied the abbreviated mFI (amFI) in a retrospective database study including 1928 patients that had un-dergone pancreatic and liver surgery for the most part. This amFI consists ofﬁve variables only: 1. COPD, 2. CHF in 30 days before surgery, 3. partial or totally dependent functional status, 4. hyper-tension, and 5. diabetes. The frailty score was categorized as 0, 1, or 2. A score of 2 was associated with an increased risk of post-operative complications. Ramanathan [23] added age>70 y to the amFI and showed that this predicted the discharge disposition of cancer patients including hepatobiliary patients. All studies con-cerning the rFI, mFI and its adaptations were done retrospectively in the American College of Surgeons NSQIP database.

In one of the few prospective studies on the subject, Ishihara [25] and Tanaka [24] investigated the predictive value of the Kihon checklist. The checklist predicted postoperative loss of indepen-dence (deﬁned as transfer to a rehabilitation facility, discharge to residence with home-based healthcare, 30-day readmission for poor functionality, and 90-day mortality), but not the occurrence of postoperative delirium.

Summary and conclusions

An increasing number of studies have investigated the relation between preoperative frailty screening tools, GA and postoperative outcomes after HBP surgery in older patients with cancer, but the evidence is still limited. The studies are mostly retrospective, and the few prospective studies are small. It seems frailty is not yet a routine part of the clinical decision making process in HBP surgery. However, the results consistently indicate that frailty is a powerful negative predictor for postoperative outcomes. As frailty is deﬁned by the accumulation of deﬁcits such as functional and cognitive impairment, comorbidities, reduced mobility and malnutrition, it provides improved prediction compared to chronological age alone [2]. Reduced functional status, measured by the ability to perform ADLs or exhaustion, stands out as the most consistent predictor of negative outcomes from the available studies. Less is known about the impact of cognitive function, and since cognition also has an impact on decision-making capacity, this factor warrants more study. Although the perfect frailty screening tool will probably never been found, it seems that the time has arrived to start changing the decision-making process in HBP surgery from a medical-technical one, to a process involving all aspects of the patient, including frailty.

Declaration of competing interest

The authors have no conﬂicts of interest to declare. References

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