Thoracic Surgery with Geriatric Assessment and Collaboration can Prepare Frail Older Adults for Lung Cancer Surgery

Abstract

Background and Objectives:

We assessed frailty, measured by a comprehensive-geriatric assessment-based frailty index (FI-CGA), and its association with post-operative outcomes among older thoracic surgical patients.

Methods:

Patients aged ≥65 years evaluated in the geriatric-thoracic clinic between June 2016 through May 2020 who underwent lung surgery were included. Frailty was defined as FI-CGA >0.2, and “occult frailty”, a level not often recognized by surgical teams, as 0.2 < FI-CGA ≤ 0.4. A qualitative analysis of geriatric interventions was performed.

Results:

73 patients were included: 45 (62%) were non-frail and 28 (38%) were frail. “Occult frailty” was present in 23/28 )82%). 61 (84%) had lung malignancy. Geriatric interventions included delirium management, geriatric-specific pain and bowel regimens, and frailty optimization. More sub-lobar resections vs. lobectomies (61% vs. 25%) were performed among frail patients. Frailty was not significantly associated with overall complications (OR 2.4, 95% CI 0.88–6.44; p=0.087), major complications (OR 2.33, 95% CI 0.48–12.69; p=0.293), discharge disposition (OR 2.8, 95% CI 0.71–11.95; p=0.141), or longer hospital stay (1.3 more days; p=0.18).

Conclusion:

Frailty and “occult frailty” are prevalent in patients undergoing lung surgery. However, with integrated geriatric management, these patients can safely undergo surgery.

INTRODUCTION

In the United States, adults ≥60 years old account for >70% of those undergoing major lung resection.¹ The majority of these procedures are performed for staging and treatment of lung cancer.¹

As chronologic age is recognized as insufficient to stratify surgical risks, many professional societies recommend performing a comprehensive geriatric assessment (CGA) prior to making treatment decisions in older adults to measure frailty and tailor treatment plans.^2–4 Frailty, a state of decreased physiologic reserve resulting in diminished capacity to maintain homeostasis after a stressor, is associated with increasing age.⁵ The two most widely-studied approaches to measuring frailty are the frailty phenotype and deficit accumulation.^6–8 A deficit accumulation frailty index (FI) is a summative measure of the deficits accumulated across different health domains. It can be constructed using data from the CGA and applying rigorous rules to define the variables used to construct the index.⁹ The CGA-based frailty index (FI-CGA) has been shown to be an effective tool to measure vulnerabilities in health domains and predict significant outcomes in a variety of patient populations.^10,11 In addition, pre-operative geriatric assessment has been found to improve post-operative outcomes such as shortening length of stay (LOS).¹²

When assessing candidates for thoracic surgery, current guidelines recommend evaluating pulmonary function tests, comorbidities, and performance status prior to lung resection.^13,14 Frailty is common among older patients who are candidates for thoracic surgery¹⁵ and can adversely affect surgical outcomes and long-term survival,^15,16 yet a multidisciplinary team that includes an embedded geriatrician in the pre-operative setting is not widely utilized.

The purpose of this study was to assess the prevalence of frailty measured by FI-CGA among older surgical patients in a geriatric thoracic clinic and assess the correlation of frailty with post-operative outcomes. In addition, we describe the rate of “occult frailty,” which we defined as levels of frailty often un-recognized by surgical teams.

PATIENTS AND METHODS

Cohort selection

Patients aged 65 years and older presenting to a geriatric thoracic clinic at the Brigham and Women’s Hospital between June 2016 through May 2020 who received a CGA by a board-certified geriatrician were included. The CGA includes assessment of co-morbidities, function, cognition, psycho-social factors, and medications. Patients who did not undergo surgery or did not undergo major lung resection surgery (e.g., received lymph node biopsy without resection) were excluded. Patients who underwent esophageal procedures were also excluded due to the vast differences between lung and esophageal surgery outcomes. All procedures were performed by a single surgeon.

Data elements

Pre-operative variables included baseline demographic information, social history, pre-operative forced expiratory volume in 1 second (FEV1), surgical intent, and FI-CGA variables (health deficits). The FI-CGA was constructed using 63 total possible health deficits spanning multiple geriatric domains, adapted from a previously validated FI-CGA.^16,17 Our FI-CGA included 18 comorbidities (Appendix 1) and 45 additional domains including: functional status measured by activities of daily living (ADL’s) and instrumental ADLs (IADL’s), cognitive status measured by Mini-Cog¹⁸ and collateral history, delirium measured by the 3D-CAM test,¹⁹ medication review, and psycho-social evaluation. One point was added to the score for each comorbidity (saturated at 18 points) and each of the 45 domains were coded between 0–1. The sum of the score was divided by the total number of non-missing deficits to generate a final FI-CGA between 0–1 (Appendix 2).

Patients were categorized as non-frail (FI-CGA ≤ 0.2) and frail (FI-CGA > 0.2).²⁰ We referred to “occult frailty” as a frailty level often missed by surgical teams, since a full CGA is necessary to recognize milder degrees of frailty. A score of 0.2 < FI-CGA ≤ 0.4 was used to define “occult frailty” in our frail group, as higher degrees of frailty (FI-CGA >0.4; severe frailty) are typically recognized by the team even if not always defined. In addition, we used the Social Vulnerability Index (SVI) to evaluate the level of supports and relationships patients had prior to surgery.²¹ SVI was generated using data on key relationships, living situation, caregiver availability and burden, all of which were collected during the CGA.

Surgical variables including technique and intent were collected. All post-operative complications were prospectively collected in a computerized database by the thoracic surgery team and routinely audited by attendings within the division. Post-operative complications were graded using the Clavien-Dindo system.²² In our study, grade II and higher were considered meaningful complications and grade III and higher were considered major complications. Grade I complications were not collected. Hospital LOS, discharge disposition (home, home with services, and inpatient rehabilitation), and pathologic cancer stage were collected. Specific complications such as aggregated pulmonary complications (defined as air leak lasting longer than 5 days, acute respiratory distress syndrome, pulmonary embolism, pneumonia), atrial fibrillation, delirium, and urinary retention were also documented. This study was approved by the Institutional Review Board at Mass General Brigham #2016P002360.

Qualitative analysis of geriatrics-guided interventions

A qualitative analysis of additional geriatric assessments and interventions made during the initial geriatric consult was performed. Using the grounded theory process,²³ consult notes were reviewed and geriatric-specific categories regarding counseling and perioperative recommendations were collected. Axial coding was performed to create conceptual themes, followed by selective coding to turn themes into a formal framework with coded variables. Two reviewers independently evaluated each geriatric consult note for these themes. Finally, two reviewers summarized and reviewed the data with an independent adjudicator resolving areas with low agreement by re-reviewing the medical note. Each category was described with a proportion of patients who received the intervention.

Statistical analysis

Statistical analysis was performed using R version 4.0.2.²⁴ The Fisher exact test for categorical variables and the Wilcoxon Rank Sum test for continuous variables were used to compare baseline characteristics between frail and non-frail patients. Univariable linear regression was performed to quantify the possible relationship between frailty and hospital LOS, measured as a continuous variable in years. A univariable logistic regression analysis was performed to determine the association between frailty and pre-determined outcomes including any complication, major complications, specific complications listed above, and discharge disposition. Significance for 2-tailed tests was set at p<0.05.

RESULTS

Overall, 144 patients were seen in the multidisciplinary geriatric-surgical thoracic clinic from May 2016 to January 2020. Of these, 73 were included in the final analysis. 45 patients (62%) were considered non-frail and 28 (38%) frail. Occult frailty was present in 23/28 frail patients (82%) (Figure 1). Baseline characteristics were similar between the frail and non-frail groups, with an overall median age of 77 years (range 51–96), 51% female, and a similar BMI distribution between the two groups (Table 1). FEV1 was not significantly different between the groups: median 79% vs. 73% respectively (p=0.315). There was a significant difference in SVI distribution between the two groups, as a significantly greater percentage of non-frail patients had high social vulnerability scores compared to those with frailty (20% vs. 11%, p=0.041). Patients with frailty were more dependent in basic daily living activities (ADL) (64% vs 20%, p<0.001) and instrumental daily activities (IADL) as compared to non-frail patients (75% vs. 31%, p<0.001). The mean number of comorbidities was significantly higher in patients with frailty (4.75 vs. 3.67, p<0.001). The mean number of pulmonary-specific comorbidities was also significantly higher in those with frailty (0.35 vs. 0.79, p=0.003). There was a significantly lower mean (SD) pre-operative albumin in those with frailty compared to those without (4.02 (0.50) vs. 4.25 (0.27), p=0.006). There was also a higher prevalence of cognitive impairment in the frail group, specifically more mild cognitive impairment (58% vs 17%, p<0.001) and dementia (4.2% vs 0%). Higher rates of mini-cog scores of 2 and below in those with frailty did not reach statistical significance (21% vs. 2%, p=0.056) (Table 1).

Figure 1.

Frailty distribution among cohort of 73 patients.

Table 1.

Baseline Characteristics

	Non-Frail (N=45)	Frail (N=28)	Overall (N=73)	P-value
Age (y)
Median [Interquartile Range]	76.7 [72.3, 80.6]	76.5 [72.4, 80.2]	76.7 [72.3, 80.5]	0.533a
Female Sex	25 (55.6%)	12 (42.9%)	37 (50.7%)	0.341b
Race
White	38 (84.4%)	26 (92.9%)	64 (87.7%)	0.490b
Black or African American	3 (6.7%)	1 (3.6%)	4 (5.5%)
Other	3 (6.7%)	0 (0%)	3 (4.1%)
Missing	1 (2.2%)	1 (3.6%)	2 (2.7%)
BMI Category
Underweight	1 (2.2%)	2 (7.1%)	3 (4.1%)	0.323b
Normal Weight	17 (37.8%)	6 (21.4%)	23 (31.5%)
Overweight	16 (35.6%)	9 (32.1%)	25 (34.2%)
Obese	11 (24.4%)	10 (35.7%)	21 (28.8%)
Missing	0 (0%)	1 (3.6%)	1 (1.4%)
Social Vulnerability Index (SVI)
Low	9 (20.0%)	1 (3.6%)	10 (13.7%)	0.041b
Medium	26 (57.8%)	24 (85.7%)	50 (68.5%)
High	9 (20.0%)	3 (10.7%)	12 (16.4%)
Missing	1 (2.2%)	0 (0%)	1 (1.4%)
Forced Expiratory Volume in 1 Second (FEV1)
Median [Interquartile Range]	79.0 [66.0, 93.0]	72.5 [62.3, 89.3]	76.0 [64.5, 92.0]	0.315a
Pre-Operative Serum Albumin (g/dL)
Mean (Standard Deviation)	4.25 (0.27)	4.02 (0.50)	4.16 (0.39)	0.006a
Missing (%)	5 (11.1%)	2 (7.1%)	7 (9.6%)
Any Activities of Daily Living (ADL) Assist/Dependency	9 (20.0%)	18 (64.3%)	27 (37.0%)	<0.001b
Any Independent Activities of Daily Living (IADL) Assist/Dependency	14 (31.1%)	21 (75.0%)	35 (47.9%)	<0.001b
Number of Comorbidities*
Mean (Standard Deviation)	3.67 (1.62)	4.75 (1.92)	4.08 (1.81)	<0.001a
Number of Cardiac Comorbidities** Mean (Standard Deviation)	1.16 (0.95)	1.43 (1.10)	1.26 (1.01)	0.295a
Number of Pulmonary Comorbidities** Mean (Standard Deviation)	0.36 (0.53)	0.79 (0.63)	0.52 (0.60)	0.003a
Mini-Cog
5	26 (57.8%)	14 (50.0%)	40 (54.8%)	0.056b
4	11 (24.4%)	4 (14.3%)	15 (20.5%)
3	5 (11.1%)	2 (7.1%)	7 (9.6%)
<=2	1 (2.2%)	6 (21.4%)	7 (9.6%)
Missing	2 (4.4%)	2 (7.1%)	4 (5.5%)
Cognitive Status
Within Normal Limits	34 (82.9%)	9 (37.5%)	43 (66.2%)	<0.001b
Mild Cognitive Impairment	7 (17.1%)	14 (58.3%)	21 (32.3%)
Dementia	0 (0%)	1 (4.2%)	1 (1.5%)
Body Mass Index (BMI) Categories, per World Health Organization classifications:  Underweight: BMI < 18.5  Normal Weight: 18.5 ≤ BMI < 25  Overweight: 25 ≤ BMI < 30  Obese: BMI ≥ 30 Social Vulnerability Index  Low: SVI < 0.0275  Medium: 0.0275 ≤ SVI < 0.464  High: 0.464 ≤ SVI < 1

p-values obtained from:

^aWilcoxon Rank Sum Test

^bFisher Exact Test

^*Comorbidities as listed in Appendix 1

^**Cardiovascular comorbidities tabulated include coronary artery disease, atrial fibrillation, congestive heart failure, peripheral vascular disease, and hypertension. Pulmonary comorbidities tabulated include asthma, chronic obstructive pulmonary disease, and interstitial lung disease.

Of the 73 patients included, 61 (84%) patients had a diagnosis of cancer. In both groups, the majority had non-small cell lung cancer (NSCLC) (67% of non-frail vs. 54% of frail, p=0.58), with no statistically significant differences in pathologic stage (Table 2). Lobectomy was the most performed procedure (41%), followed by wedge resection (36%), segmentectomy (12%), and pleurectomy (11%). Patients with frailty underwent significantly higher rates of sub-lobar resection (61% vs. 40%) compared to lobectomy (25% vs. 51%; p=0.025). There was no significant difference in surgical technique in those without and with frailty: thoracotomy was used in 18% vs. 25%, while video-assisted thoracoscopic surgery was used in 82% vs. 75% (p=0.56). There were also no significant differences in surgical intent between those with and without frailty: Curative intent was the most common reason for undergoing surgery in both groups (82% vs. 84%, p=0.840), followed by staging (18% vs 13%, respectively) (Table 3). There was no significant difference in mean (SD) operative time (142 (110) vs. 147 (110) minutes, p=0.84), estimated blood loss (208 (251) vs. 201 (420) mL, p=0.09) in those with and without frailty.

Table 2.

Oncologic Variables (n=61)

	Non-Frail (N=45)	Frail (N=28)	Overall (N=73)	P-valuea
Cancer Patient	40 (88.9%)	21 (75.0%)	61 (83.6%)	0.225
Tumor Grade
G1: Low Grade	5 (11.1%)	0 (0%)	5 (6.8%)	0.358
G2: Intermediate Grade	7 (15.6%)	6 (21.4%)	13 (17.8%)
G3: High Grade	10 (22.2%)	4 (14.3%)	14 (19.2%)
GX: Undetermined Grade	17 (37.8%)	13 (46.4%)	30 (41.1%)
Missing	6 (13.3%)	5 (17.9%)	11 (15.1%)
Pathologic Stage
Tumor
T0	1 (2.2%)	0 (0%)	1 (1.4%)	0.886
T1	20 (44.4%)	12 (42.9%)	32 (43.8%)
T2	8 (17.8%)	3 (10.7%)	11 (15.1%)
T3	2 (4.4%)	1 (3.6%)	3 (4.1%)
T4	1 (2.2%)	1 (3.6%)	2 (2.7%)
TX (Metastatic – Not Lung Primary)	7 (15.6%)	4 (14.3%)	11 (15.1%)
Nodes
N0	19 (42.2%)	13 (46.4%)	32 (43.8%)	0.208
N1	4 (8.9%)	0 (0%)	4 (5.5%)
N2	4 (8.9%)	0 (0%)	4 (5.5%)
NX	12 (26.7%)	8 (28.6%)	20 (27.4%)
Metastases
M0	8 (17.8%)	4 (14.3%)	12 (16.4%)	0.494
MX	31 (68.9%)	17 (60.7%)	48 (65.8%)
Pathology
Small Cell	0 (0%)	1 (3.6%)	1 (1.4%)	0.666
Non-Small Cell	30 (66.7%)	15 (53.6%)	45 (61.6%)
Mesothelioma	3 (6.7%)	2 (7.1%)	5 (6.8%)
Metastatic (Non-Lung Primary)	6 (13.3%)	3 (10.7%)	9 (12.3%)

^ap-value calculated using chi-square test for goodness of fit

Table 3.

Operative Variables

	Non-Frail (N=45)	Frail (N=28)	Overall (N=73)	P-valuea
Surgical Technique
Thoracotomy	8 (17.8%)	7 (25.0%)	15 (20.5%)	0.555
Video-assisted Thoracoscopic Surgery (VATS)	37 (82.2%)	21 (75.0%)	58 (79.5%)
Procedure
Lobectomy	23 (51.1%)	7 (25.0%)	30 (41.1%)	0.025
Segmentectomy	2 (4.4%)	7 (25.0%)	9 (12.3%)
Wedge Resection	16 (35.6%)	10 (35.7%)	26 (35.6%)
Pleurectomy	4 (8.9%)	4 (14.3%)	8 (11.0%)
Intent
Curative	38 (84.4%)	23 (82.1%)	61 (83.6%)	0.840
Staging	6 (13.3%)	5 (17.9%)	11 (15.1%)
Palliative	1 (2.2%)	0 (0%)	1 (1.4%)
Intra-Operative Parameters
Mean Operative Time (SD) (minutes)	147 (110)	137 (113)	143 (110)	0.626
Mean Estimated Blood Loss (SD) (mL)	201 (420)	208 (251)	204 (364)	0.091
Required Blood Transfusion	4 (8.9%)	4 (14.3%)	8 (11.0%)	0.473

^ap-value calculated using chi-square test for goodness of fit

In a qualitative analysis of geriatric notes, we identified recurring geriatric-specific themes, including identification of potentially modifiable factors contributing to frailty, cognitive and mood assessments, recommendations for physical activity, optimization of medical comorbidities, and advance care planning with a focus on completing a healthcare proxy (HCP) form and Medical Orders for Life-Sustaining Treatment (MOLST) (Table 4). We tabulated recommendations regarding medication evaluation, peri-operative delirium prevention (pharmacological and non-pharmacological), and post-operative pain management and bowel regimen (Appendix 3). All (100%) patients had a frailty assessment and were counseled on their current degree of frailty and its implication on the planned surgery. In addition, all patients received counseling to increase or maintain daily physical activity prior to surgery. Social vulnerabilities were evaluated in all patients, and each received individualized counseling on necessary peri-operative and post-operative supports. Medical comorbidities were optimized in 35 (48%) patients. The importance of peri-operative nutrition especially healthy protein intake to potentially mitigate frailty and sarcopenia as well as to promote recovery was reviewed with 67 patients (92%). Non-pharmacologic ways to reduce anxiety and depression were discussed with 67 patients (92%), and ways to promote restorative sleep with 52 patients (71%). Advance care planning was discussed with 56 patients (77%), mainly focusing on the importance of establishing a HCP prior to surgery and confirming documentation in the electronic health record (EHR). Code status and MOLST were introduced and discussed with 11 patients (15%).

Table 4.

Geriatric assessments performed and recommendations made during initial geriatric consult visit.

Geriatric Domain Addressed	N (%) with whom Domain was Discussed
Assessments
Frailty using the Comprehensive Geriatric Assessment	73 (100%)
Fall within the past 6 months	69 (95%)
Medical comorbidities assessed and optimized	35 (48%)
Counseling and Discussion
Concepts of frailty discussed with patient and family	73 (100%)
Recommended daily physical activity prior to surgery	73 (100%)
Nutritional choices to increase protein intake to help reduce frailty/sarcopenia, promote recovery and resilience	67 (92%)
Non-pharmacologic ways to reduce anxiety and depression	71 (97%)
Ways to promote restorative sleep	52 (71%)
Social support assessed and discussed for peri-operative support	73 (100%)
Discussed HCP- was asked to bring forms or information given if patient did not have paperwork	56 (77%)
Medical Orders for Life-Sustaining Treatment (MOLST) was completed	11 (15%)
Peri-Operative Recommendations
Recommended to undergo pulmonary rehabilitation and/or physical therapy	18 (25%)
Medications reviewed, evaluated, and discussed potentially inappropriate medications	73 (100%)
Post-operative geriatric pain regimen (Box 1)	63 (86%)
Post-operative geriatric bowel regimen (Box 1)	65 (89%)
Post-operative non-pharmacologic delirium prevention (Box 1)	71 (97%)

Geriatric-specific peri-operative interventions were also made. All patients had their medications reviewed, and the geriatrician initiated discussion on medications that were potentially inappropriate, nonessential, or deliriogenic.²⁵ For 25% of patients, a pulmonary rehabilitation program and/or physical therapy were recommended prior to surgery with referrals to appropriate programs. Post-operative geriatric pain and bowel regimens were recommended for 86% and 89%, respectively. For 97% of patients, a post-operative non-pharmacologic delirium prevention strategy was recommended (Appendix 3).

Although patients with frailty had a higher rate of overall complications in comparison to non-frail patients (46% vs. 27%), this difference was not statistically significant (p=0.124) and was mostly attributed to grade II complications (64% of all complications). Results were similar in univariable logistic regression (OR frail vs. non-frail, 2.38, 95% CI 0.88–6.44; p=0.087). The proportion of those experiencing pulmonary complications (21% vs. 11%), delirium (14% vs. 4%), urinary retention (4% vs. 9%), and atrial fibrillation (18% vs. 9%), cardiovascular complications (25% vs. 13%), or need for intraoperative transfusion (14% vs. 9%) was not statistically significantly different between patients with and without frailty (all p>0.05). Days (4.8 vs. 4.3) in the intensive care unit (ICU), mean daily volume (245 vs. 249 cc) of drainage from the intercostal chest tube, mean days (3.6 vs. 3.4) of intercostal chest drainage, or need for reoperation due to complications (7.1 vs. 4.4%) was not statistically significantly different between those with and without frailty (all p>0.05). There were 3 patients in the frail group and 0 in the non-frail group who had unplanned ICU admissions. Cardiovascular complications recorded included myocardial infarction, right ventricular failure, and deep vein thromboses. Pulmonary complications recorded included air leaks lasting longer than 5 days, hemothorax, respiratory failure, pneumonitis, pleural effusion, chylothorax, and right middle lobe collapse. Three patients had complications that required an admission into the intensive care unit: one in the non-frail group (myocardial infarction) and two in the frail group (pneumonitis causing respiratory failure and right ventricular failure).

Univariable logistic regression analyses showed that among patients with frailty, the odds of experiencing grade III or higher complications were not statistically significantly higher vs. non-frail patients (OR 2.33, 95% CI 0.48–12.69; p=0.293). In addition, the odds of discharge to a facility were not statistically significantly higher among those with frailty (OR 2.80 95% CI 0.72–11.95; p=0.141). There were no post-operative surgical site infections in this cohort.

Patients with frailty had a higher median LOS, although this difference was not statistically significant (p=0.09) (Figure 2). In a linear regression model, we found that frailty was associated with increased LOS of 1.3 days more than the non-frail group; similarly, this difference was not statistically significant (p=0.094). However, LOS was associated with the procedure performed: those who received pleurectomy had considerably longer LOS compared to each of the other categories of lung procedures (all p<0.001). The LOS among those who received lobectomy, segmentectomy, and wedge resections were not significantly different (Figure 3).

Figure 2.

Distribution of length of stay (LOS) among those without and with frailty.

Figure 3.

Distribution of length of stay (LOS) among patients who underwent lung surgery.

We did not perform a multi-variable logistic regression model for these outcomes due to overall low event rates. Furthermore, from the results of the univariable logistic regression model, these outcomes were non-significantly associated with frailty, thus no added insight from a multi-variable model was expected.

Sensitivity Analysis

When changing cut-points for FI-CGA from 0.2 to 0.25, the results were similar: there was a slight decrease in the prevalence of frailty (27% were considered frail,) but LOS (1.8 more days, p=0.10) and odds of developing a post-operative complication (OR 1.89, 95% CI 0.65–5.49; p=0.24) were not significantly different between the two groups. Similarly, when changing the cut-point from 0.2 to 0.35, the results were not significantly different: although the prevalence of frailty slightly changed (12% of patients were considered frail), LOS (2.0 more days, p=0.18) and odds of developing a post-operative complication (OR 1.64, 95% CI 0.37–6.82; p=0.49) were not significantly different between the two groups.

DISCUSSION

We analyzed a cohort of older adults undergoing thoracic surgery who were evaluated and collaboratively managed by a geriatric-thoracic team. Frailty, as measured using a rigorous FI-CGA, was prevalent in our cohort (38%). Notably, most of these individuals (82%) had degrees of frailty which often are undetected by non-geriatric teams, which we defined as “occult frailty.” We identified multiple geriatric-specific interventions incorporated by the multidisciplinary team, and despite the high prevalence of frailty, these patients had similar post-operative outcomes compared to those without frailty with no evidence of higher rates of complications or longer hospital stay. Our study used a standard, yet tailored CGA-focused frailty assessment and found that with a collaborative team and appropriate interventions, a select group of frail older patients can successfully undergo definitive thoracic surgery.

The prevalence of frailty in our cohort aligns with other studies. High prevalence of pre-frailty and frailty (69% of 125 patients, defined by Fried phenotype for frailty¹⁵) was found in older candidates for surgery in a single thoracic clinic.²⁶ Interestingly, they found that the Eastern Cooperative Oncology Group (ECOG) score and frailty status were not strongly correlated, which further emphasizes the limitations of relying solely on the ECOG performance scale for treatment decisions and risk assessment.²⁶ Another example supporting the importance of rigorously assessing and identifying varying degrees of frailty typically undetected by non-geriatric teams is a study by Ferguson et al. showing that surgeons and trainees consider clinical judgement based on physical appearance and behavior (the “eyeball test”) more important than clinical factors.²⁷ Conducting a CGA in older patients allows clinical, psycho-social, and physical factors to be addressed peri-operatively, while assuring that validated geriatric tools, incorporated into the surgical assessment, are used to guide surgical decisions rather than “eyeballing” the patient. Studies on older patients undergoing elective and cardiac surgery have shown that patients with frailty are at higher risk of morbidity, longer LOS, and discharge to assisted living facilities.^28–30 There is limited evidence studying the relationship between frailty and lung resection outcomes, and the literature is conflicting. Some studies show that frailty significantly correlates to higher rates of mortality, perioperative complications, and post-operative renal failure,^7,31 while others show no significant differences in LOS and discharge disposition when compared to non-frail patients,^32,33 similar to our results.

We found no evidence of increased overall complication rates in the frail group compared to the non-frail group (46% vs. 27%; p=0.124), and the complications experienced by patients in our cohort were predominantly minor complications (grade II- 64% of all complications in the frail group). Furthermore, our rates of grade IV complications were 2 folds lower than previously described.⁷ Our findings are due to many contributing factors: most patients in our cohort had mild to moderate frailty which may represent a less frail sub-group with overall favorable outcomes; frail patients had a tailored surgical approach with 50% fewer lobectomies as compared to non-frail patients (25% vs. 51%) and higher rates of minimally invasive techniques with lung preservation (segmentectomies and wedge resections). Our results may also be explained, at least in part, by the presence of geriatric collaboration, which allowed assessment and interventions to be employed perioperatively. This approach is supported by a recent study demonstrating that geriatric assessment-guided care enhances collaboration across multiple disciplines and is associated with reduced post-operative 90-day mortality in older adults with cancer.³⁴

The definition of frailty varied among studies examining the association between frailty and post-operative outcomes. As discussed previously, we used the FI-CGA and defined frailty by using a cutoff of FI-CGA > 0.2. Others used FI-CGA to measure frailty in older cancer patients receiving chemotherapy, and found that 39% of patients had an FI-CGA of 0.2–0.35.³⁵ In this study, they used 0.35 as a cutoff for the presence of frailty, so these patients were categorized as pre-frail. Other FI-CGA cutoff values are used to define and grade frailty such as FI-CGA >0.25 and FI-CGA>0.35 for moderate-severe frailty. ^36,37 When applying other cutoff values as described in our sensitivity analysis, the results did not change profoundly, so we believe this truly represents the relationship of frailty to surgical outcomes in our cohort of patients.

In our qualitative analysis, all patients had a FI-CGA that not only includes physical frailty and comorbid health conditions, but also other aspects of aging such as cognition, functional status, psychosocial assessment, medication review, and a physical examination to create a multi-domain frailty assessment that helps to guide geriatric interventions.¹⁷ These discussions and recommendations on delirium prevention and management, peri-operative pain and bowel regimens, medication review, and discussions on potentially preventing progression and/or reducing frailty may have successively resulted in improved post-operative outcomes, further explaining the overall favorable outcomes in our cohort and supporting collaborative approaches for delivering care to older surgical patients. The discussion on advanced care planning prior to surgery in older patients is important.³⁸ In our cohort, 77% of patients had a discussion on assigning or confirming a designated HCP, and 15% of patients had a MOLST form completed during the visit. Although these rates are lower than other domains discussed in the CGA, it was higher than expected, as a recent study showed that less than 2% of older patients undergoing elective surgery had a completed MOLST form documented.³⁹ This further emphasizes the importance of discussing and documenting patients’ preferences, trade-offs, priorities and expected treatment goals,^40–42 specifically, as the American College of Surgeons and the American Geriatric Society have launched the Geriatric-Surgery Verification program (GSV), requiring these discussions to be explicitly documented in the electronic health record (EHR).⁴³

Lastly, we found that most frail patients (89%) had low to medium SVI indicating the presence of stronger social supports (decreased caregiver burden, living with someone and having access to frequent support if needed). This also may have contributed to the better-than-expected outcomes after surgery in frail patients, as it was previously shown that higher social vulnerability is associated with increased risk of worse post-operative outcomes while good social supports can mitigate the adverse effects of frailty on short and long term outcomes.^44,45 Although our current study was not powered to adjust outcomes by SVI, this reinforces that having good social supports can counteract some of the negative effects of frailty on health outcomes.⁴⁶

Our study had several limitations. First, our study cohort included only operative patients at a large volume academic center, and all surgeries were performed by a single surgeon. This may limit the generalizability of our findings, excluding those who did not undergo surgery for various reasons. Our clinicians in the geriatric thoracic clinic used the geriatric assessment to inform selection of patients for surgery (versus non-operative management), and the number of patients for whom a non-operative strategy was recommended was not captured. This may have excluded frail patients who may have had higher rates of complications than those observed in our study. Furthermore, this cohort was predominantly Caucasian (88%), and 84% had a diagnosis of lung cancer, predominantly low-grade malignancies. Future studies should evaluate these results in larger, diverse cohorts and amongst different surgical-oncology services. Second, all patients had a geriatric assessment and multiple interventions, which must be considered when generalizing our findings to other surgical settings, especially those without access to a geriatrician. Lastly, this is a retrospective study, so all geriatric variables and interventions were collected from EHRs, while the surgical variables including post-operative complications were from a prospectively collected database.

CONCLUSION

Frailty and “occult frailty”, as defined by FI-CGA, are prevalent in patients undergoing lung surgery. Despite this, with integrated geriatric assessment and management, frail older patients can undergo lung surgery without increased complication rates compared to their non-frail counterparts. We provide preliminary evidence suggesting that, if carefully selected and optimized, frail patients with early-stage lung cancer can receive the benefits of definitive lung surgery while minimizing adverse events. Our findings call for larger, multi-site studies that compare geriatrics- and frailty-guided surgical management with standard surgical management, from pre-operative assessment to post-operative outcomes, including mortality. Such studies will shed light on the effectiveness of different models of integrated geriatrics care, informing more widespread implementation with the ultimate goal of better patient selection and outcomes in older adults with thoracic malignancies.

Synopsis:

Frailty is prevalent among our cohort of older adults undergoing major lung resection. With incorporation of geriatricians who perform pre-operative optimization and peri-operative management, patients with frailty underwent lung surgery without increased post-operative complications or length of stay compared to their non-frail counterparts.