Effect of an Oncology Nurse–Led Primary Palliative Care Intervention on Patients With Advanced Cancer: The CONNECT Cluster Randomized Clinical Trial

Yael Schenker; Andrew D Althouse; Margaret Rosenzweig; Douglas B White; Edward Chu; Kenneth J Smith; Judith M Resick; Shane Belin; Seo Young Park; Thomas J Smith; Marie A Bakitas; Robert M Arnold

doi:10.1001/jamainternmed.2021.5185

. 2021 Sep 13;181(11):1–10. doi: 10.1001/jamainternmed.2021.5185

Effect of an Oncology Nurse–Led Primary Palliative Care Intervention on Patients With Advanced Cancer

The CONNECT Cluster Randomized Clinical Trial

Yael Schenker ^1,^2,^✉, Andrew D Althouse ³, Margaret Rosenzweig ^2,⁴, Douglas B White ^2,⁵, Edward Chu ⁶, Kenneth J Smith ³, Judith M Resick ^1,², Shane Belin ^1,², Seo Young Park ⁷, Thomas J Smith ⁸, Marie A Bakitas ⁹, Robert M Arnold ^1,²

¹Division of General Internal Medicine, Section of Palliative Care and Medical Ethics, University of Pittsburgh, Pittsburgh, Pennsylvania

²Palliative Research Center, University of Pittsburgh, Pittsburgh, Pennsylvania

³Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania

⁴University of Pittsburgh School of Nursing, Pittsburgh, Pennsylvania

⁵Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania

⁶Albert Einstein Cancer Center, Albert Einstein College of Medicine, New York, New York

⁷Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea

⁸Division of General Internal Medicine, Section of Palliative Medicine, Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland

⁹School of Nursing, UAB Center for Palliative and Supportive Care, University of Alabama at Birmingham, Birmingham

Accepted for Publication: July 25, 2021.

Published Online: September 13, 2021. doi:10.1001/jamainternmed.2021.5185

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Corresponding Author: Yael Schenker, MD, MAS, Palliative Research Center, University of Pittsburgh, 230 McKee Pl, Ste 600, Pittsburgh, PA 15213 (yas28@pitt.edu).

Author Contributions: Dr Althouse had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Schenker, Rosenzweig, White, Chu, K. J. Smith, T. J. Smith, Arnold.

Acquisition, analysis, or interpretation of data: Schenker, Althouse, Rosenzweig, White, Chu, Resick, Belin, Park, T. J. Smith, Bakitas.

Drafting of the manuscript: Schenker, Althouse, Resick, Belin, Park, T. J. Smith, Arnold.

Critical revision of the manuscript for important intellectual content: Schenker, Althouse, Rosenzweig, White, Chu, K. J. Smith, Resick, Park, T. J. Smith, Bakitas.

Statistical analysis: Althouse, Park.

Obtained funding: Schenker.

Administrative, technical, or material support: White, Chu, Resick, Belin, Arnold.

Supervision: Chu, Belin, T. J. Smith, Arnold.

Other - oncologist perspective: T. J. Smith.

Conflict of Interest Disclosures: Dr Schenker reported receiving personal fees from UpToDate Inc outside the submitted work. Dr White reported receiving honorarium from the American Thoracic Society and personal fees from UpToDate Inc outside the submitted work. Dr T. J. Smith reported receiving grants from the Patient-Centered Outcomes Research Institute and an honorarium from the Association of Community Cancer Centers. Dr Arnold reported receiving personal fees as editor of the palliative care section from UptoDate Inc and personal fees as editor of PC FACS from the American Academy of Hospice and Palliative Medicine outside the submitted work. No other disclosures were reported.

Funding/Support: This trial was supported by grant R01CA197103 from the National Cancer Institute of the National Institutes of Health (principal investigator: Dr Schenker). This trial also used resources provided through the Cancer Center Support Grant P30CA047904 from the National Cancer Institute.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 3.

Additional Contributions: We thank the referring oncologists, the CONNECT nurses, and clinical staff at the UPMC Hillman Cancer Center; the nursing leadership, especially Terri Frassinelli, BSN, RN, OCN; the clinical research operations staff and leadership, especially Bhanu Pappu, PhD, MHA, and Donna Haney, BSN, RN, OCN; and Peter Ellis, MD, Robert Ferris, MD, PhD, and Stanley Marks, MD, for their guidance and support. We also thank the CONNECT research staff, including Caroline Sefcik, BA, Kelsey Vukic, BS, and Carolyn Impagliazzo, BS, for their hard work and dedication to the CONNECT project, and Ethan Lennox, MA, for editorial support. These individuals received no additional compensation outside of their usual salary for their contributions.

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Corresponding author.

PMCID: PMC8438619 PMID: 34515737

This cluster randomized clinical trial evaluates the quality of life, symptom burden, and anxiety and depression reported by adults with advanced cancer who were receiving a primary palliative care intervention.

Key Points

Question

Does a primary palliative care intervention that is delivered by infusion room nurses who are part of an oncology clinic’s clinical team improve outcomes for patients with advanced cancer?

Findings

In this cluster randomized clinical trial involving 672 patients with metastatic solid tumors, an oncology nurse–led primary palliative care intervention did not improve quality of life compared with standard oncological care alone.

Meaning

Primary palliative care interventions with a higher dose intensity may be necessary to improve outcomes for most patients with advanced cancer who lack access to palliative care specialists.

Abstract

Importance

Guidelines recommend early specialty palliative care for all patients with advanced cancer, but most patients lack access to such services.

Objective

To assess the effect of CONNECT (Care Management by Oncology Nurses to Address Supportive Care Needs), a primary palliative care intervention delivered by oncology nurses, on patient outcomes.

Design, Setting, and Participants

This cluster randomized clinical trial of the CONNECT intervention vs standard care was conducted from July 25, 2016, to October 6, 2020. Participants were adult patients with metastatic solid tumors who were undergoing oncological care and for whom an oncologist would agree with the statement “would not be surprised if the patient died in the next year.” The trial was conducted at 17 community oncology practices in western Pennsylvania. Data analyses adhered to the intention-to-treat principle.

Interventions

The CONNECT intervention included 3 monthly visits with an existing infusion room nurse who was trained to address symptoms, provide emotional support, engage in advance care planning, and coordinate care.

Main Outcomes and Measures

The primary outcome was quality of life. At baseline and 3 months, participants completed assessments of quality of life (Functional Assessment of Chronic Illness Therapy-Palliative care: score range, 0-184, with higher scores indicating better quality of life), symptom burden (Edmonton Symptom Assessment Scale: score range, 0-90, with higher scores indicating greater symptom burden), and mood symptoms (Hospital Anxiety and Depression Scale [HADS]: score range, 0-21, with higher scores indicating substantial anxiety and depression). Linear mixed-effects models were used to estimate adjusted mean differences in 3-month outcomes. Preplanned, intensity-adjusted analyses were conducted.

Results

A total of 672 patients were enrolled (mean [SD] age, 69.3 [10.2] years; 360 women [53.6%]). The mean (SD) number of CONNECT visits completed was 2.2 (1.0). At 3 months, no difference in mean (SD) quality-of-life score was found between the CONNECT and standard care groups (130.7 [28.2] vs 134.1 [28.1]; adjusted mean difference, 1.20; 95% CI, −2.75 to 5.15; P = .55). Similarly, there was no difference between groups in 3-month mean (SD) symptom burden (23.2 [16.6] vs 24.0 [16.1]; adjusted mean difference, −2.64; 95% CI, −5.85 to 0.58; P = .11) or mood symptoms (HADS depression subscale score: 5.1 [3.4] vs 4.8 [3.7], adjusted mean difference, −0.08 [95% CI, −0.71 to 0.57], P = .82; HADS anxiety subscale score: 5.7 [3.9] vs 5.4 [4.2], adjusted mean difference, −0.31 [95% CI, −0.96 to 0.33], P = .34). Intensity-adjusted analyses revealed a larger estimated treatment effect for patients who received a full dose (3 visits) of the CONNECT intervention.

Conclusions and Relevance

This cluster randomized clinical trial found that a primary palliative care intervention that was delivered by oncology nurses did not improve patient-reported outcomes at 3 months. Primary palliative care interventions with a higher dose intensity may be beneficial for most patients with advanced cancer who lack access to palliative care specialists.

Trial Registration

ClinicalTrials.gov Identifier: NCT02712229

Introduction

Patients with advanced cancer experience steep declines in quality of life because of their physical and emotional symptoms.^1,2 Inadequate attention to symptom control and lack of emotional support within the standard oncological care contribute to morbidity in this population.^3,4,5 Early specialty palliative care (SPC) has been reported to improve patient outcomes in select randomized clinical trials.^6,7,8,9,10 In response to a growing evidence base, guidelines recommend SPC for all patients with an advanced cancer diagnosis.¹¹ However, workforce shortages make it impossible for palliative care specialists to care for more than a small percentage of these patients.^12,13,14 Innovative models are needed to improve the provision of primary palliative care, defined as basic symptom management and communication skills delivered by clinicians who are not palliative care specialists, within oncology practices.¹⁵ The evidence base for primary palliative care interventions is limited, with many trials showing a high risk of bias (as assessed using the Cochrane Collaboration’s risk-of-bias tool)^16,17 and primarily focusing on inpatient or home settings.¹⁶ Thus, rigorous evaluation of primary palliative care interventions in outpatient oncology settings is needed.

We developed, manualized, and pilot-tested a primary palliative care intervention called CONNECT (Care Management by Oncology Nurses to Address Supportive Care Needs).^18,19 CONNECT draws on successful care management strategies by training the clinical team’s infusion room nurses to address deficient care processes within their oncology practices. To assess the effect of CONNECT on patient outcomes, we conducted a cluster randomized clinical trial. We hypothesized that patients who receive CONNECT would have (1) improved quality of life (primary outcome), (2) decreased symptom burden, and (3) decreased symptoms of anxiety and depression.

Methods

From July 25, 2016, to October 6, 2020, we conducted a single-blind, cluster randomized clinical trial of the CONNECT intervention vs standard care (control). We followed the Consolidated Standards of Reporting Trials (CONSORT) reporting guideline. The University of Pittsburgh Institutional Review Board approved all study procedures before enrollment was initiated. All patients provided written informed consent, and caregivers were allowed to give verbal consent. Details of the study design have been published elsewhere,¹⁸ and the full protocol is available in Supplement 1.

Setting and Patient Participants

We conducted the trial at 17 community general medical oncology practices within the University of Pittsburgh Medical Center Hillman Cancer Center Network in western Pennsylvania (UPMC Hillman Cancer Center–Beaver, Beaver; UPMC Horizon–Farrell, Farrell; IRMC Cancer Center–Indiana, Indiana; UPMC Hillman Cancer Center–West Mifflin, West Mifflin; UPMC Mercy, Pittsburgh; UPMC Hillman Cancer Center–Monroeville, Monroeville; UPMC McKeesport, McKeesport; UPMC Hillman Cancer Center at John P Murtha Pavilion, Johnstown; UPMC Hillman Cancer Center–New Castle, New Castle; UPMC Northwest, Seneca; UPMC Hillman Cancer Center–Norwin, North Huntingdon; UPMC Hillman Cancer Center–Greensburg, Greensburg; UPMC Passavant–McCandless [OHA], Pittsburgh; UPMC Passavant–McCandless [HOA], Pittsburgh; UPMC Hillman Cancer Center–Bethel Park, Bethel Park; UPMC Hillman Cancer Center–Uniontown, Uniontown; UPMC Hillman Cancer Center–Washington, Washington). The Hillman Cancer Center Network serves more than 90 000 patients annually, and 7% to 8% of this patient population are members of racial/ethnic minority groups. Because our goal was to evaluate a primary palliative care intervention for patients who lacked easy access to SPC, eligible sites did not have a co-located SPC clinic at the time of study initiation.

Eligible patients were adults (aged ≥21 years) with metastatic solid tumors for whom the oncologist would agree with the statement “would not be surprised if the patient died in the next year.”^20,21,22 This question was answered by oncologists electronically as part of their clinical workflow and then confirmed by the study team before patient enrollment. We included patients who reported that they were planning to receive ongoing care from a participating oncologist and willing to be seen at least monthly. We excluded patients with an Eastern Cooperative Oncology Group (ECOG) Performance Status score of 3 or higher (being in a bed or chair >50% of waking hours) and those with cognitive impairment or inability to consent to treatment as determined by their oncologist. In the pilot work, these criteria successfully identified patients who had sufficiently advanced disease to warrant the provision of palliative care but who were not too ill to participate in the trial.¹⁹ We also excluded patients with hematologic malignant neoplasms, given the unique challenges of palliative care provision in this population (eg, unpredictable disease trajectories),²³ and those who were unable to read and respond to questions in English. Patients were encouraged but not required to identify a caregiver to participate; a caregiver was defined as an adult family member or friend who most likely would accompany them to oncology clinic visits or help with their care when needed. Caregiver outcomes will be reported in the future.

Randomization and Enrollment

We chose the oncology clinic as the unit of randomization because CONNECT is naturally applied at the practice level. The oncology clinic was defined as a unique location and clinician group for outpatient oncological care. The unit of analysis was the individual patient. Our study statistician (S.Y.P.) generated the 1:1 randomization sequence, using R version 3.2.3 (R Foundation for Statistical Computing), stratified by practice size. We identified potentially eligible patients by searching upcoming appointment lists for patients with metastatic solid tumors whose oncologists “would not be surprised if the patient died in the next year.” Study staff and participating oncologists verified patient eligibility. To avoid recruitment bias, we informed participants of their site’s randomization group after completing the informed consent form and baseline questionnaires.

We screened 3026 patients at 17 oncology clinics (Figure). Of these patients, 672 were enrolled, 516 declined participation, 736 were ineligible, and 1102 were not approached. Patients who declined participation did not differ from those who were enrolled in terms of age, race and ethnicity, or sex (eTable 1 in Supplement 2). Race and ethnicity information was self-reported by participants.

CONNECT Intervention

Conceptually grounded in the chronic care model described by Wagner and colleagues,^24,25 CONNECT used an oncology nurse–led care management approach to improve the provision of primary palliative care within outpatient oncology practices. Across 9 oncology clinics, we selected 23 infusion room nurses with existing clinical roles to be trained in the CONNECT intervention. To account for potential nursing turnover, we trained 2 or more nurses per site and offered the training 6 times over the study period. A structured curriculum was delivered in person over 3 days and focused on (1) symptom assessment and management, (2) emotional support, (3) advance care planning, and (4) care coordination (Supplement 1 includes the intervention manual and training cases). All nurses reported feeling well prepared in key skills after receiving training.²⁶

The intervention was designed to occur monthly over a 3-month period, with CONNECT visits taking place before and/or after regularly scheduled oncology clinic visits. Enrolled patients who were randomized to CONNECT met with the same nurse for all visits, and nurses had the option of conducting these visits by telephone. Nurses followed a checklist with key visit goals and communication pearls (which are summarized communication tips, such as “asking open-ended questions” and “responding to patient worries”). Following best practices in palliative oncology, the first visit focused on establishing rapport, addressing symptom needs, and choosing a surrogate decision-maker. Subsequent visits included a discussion of treatment preferences and completion of an advance directive. Visits were guided by patient-reported symptoms. Nurses worked with patients and caregivers to complete a shared care plan that detailed treatment goals and next steps. After each visit, the nurse checked in (in person, by telephone, or by email) with the patient’s oncologist about the shared care plan and conducted a follow-up telephone call with the patient to identify any problems with the plan.

All CONNECT visits were audio recorded, and 44% of these visits (296 of 675) were evaluated by a nurse project manager, following a rigorous plan to establish and maintain intervention fidelity.²⁶ Nurses received ongoing feedback on intervention fidelity through weekly telephone supervision sessions with the nurse project manager.²⁶

Standard Care

Enrolled patients who were randomized to standard care received oncology care according to best practices, including all supportive measures deemed appropriate by the oncology team. None of the participating clinics routinely administered patient-reported symptom assessment measures. Advance directives were available but not routinely discussed.

Data Collection and Patient Outcomes

Participants completed questionnaires at baseline and 3 months, either through a telephone interview or on paper. Demographic data were collected from baseline questionnaires. Oncologists assessed patient performance status. Interviewers were blinded to patient treatment group.

We measured quality of life using the Functional Assessment of Chronic Illness Therapy-Palliative care (FACIT-Pal). Combining the FACT-G (27-item Functional Assessment of Cancer Therapy-General measure of physical, social, emotional, and functional well-being) scale with a supplemental 19-item palliative care subscale to identify quality-of-life concerns for patients with life-limiting illness, the FACIT-Pal is widely used in palliative intervention trials and has shown responsiveness to change.²⁷ The FACIT-Pal scores range from 0 to 184, with higher scores indicating better quality of life.²⁸ We measured symptom burden with the Edmonton Symptom Assessment Scale (ESAS), a 9-item patient-rated instrument that was developed and validated in patients with cancer. The ESAS scores range from 0 to 10 on each item (total score 0-90), with higher scores indicating greater symptom burden.²⁹ We also used the Hospital Anxiety and Depression Scale (HADS) to measure symptoms (score range: 0-21 on each domain, with scores of ≥8 indicating substantial anxiety and depression symptoms).³⁰

Statistical Analysis

The sample size analysis incorporated an intraclass correlation coefficient because of the cluster randomized clinical trial design. For the primary outcome of change in FACIT-Pal score, we used an intraclass correlation coefficient of 0.03, which is similar to that used in a palliative care trial that randomized clinics.⁸ In an individual randomized clinical trial with 96 patients in each group, we would have 83% power to detect an effect size of 0.45 for change in the FACIT-Pal score at 3 months (n = 192 patients, with 12 patients per clinic across 16 clinics). This effect size of 0.45 translates to a clinically important difference of 11 points on the FACIT-Pal, according to reported SDs.^28,31,32 To account for the cluster trial design, we inflated the naive sample size by the design effect of (1+[(1+CV²) × m−1 × ρ]), where CV was the coefficient of variation for cluster sizes and m was the number of patients per clinic, which assumed cluster sizes were not equal across clusters.³³ The design effect using a coefficient of variation of 0.6314⁸ and number of patients per clinic of 25 increased the total sample size to 400, using 16 clusters. In addition, we accounted for 40% attrition to arrive at a number of 42 patients per clinic.

We used descriptive statistics to assess the baseline characteristics of enrolled patients and intervention delivery. Analyses for all treatment group comparisons were conducted with an intention-to-treat principle; that is, participants were analyzed according to their randomized group, regardless of how many CONNECT visits they completed. Continuous variables are reported as mean (SD), and categorical variables are reported as frequencies and percentages. We used linear mixed-effects models to estimate adjusted mean differences in continuous 3-month outcomes (FACIT-Pal, ESAS, HADS), including fixed effects for the corresponding baseline score as well as select prespecified patient characteristics (ie, age, cancer type, chemotherapy treatment, and ECOG Performance Status score) and random effects for clinic.

In addition to the primary complete case analysis, we performed 2 preplanned sensitivity analyses to assess the effect of missing data. We used multiple imputation (m = 10 imputations of missing 3-month outcome data imputed using the same covariates included in the regression model; no imputation of covariates occurred because we had 100% data completion for these variables) and a worst case single-imputation approach that assigned the worst possible score to participants who did not survive to 3 months.³⁴

We performed a preplanned, intensity-adjusted analysis to estimate the treatment effect for patients who received a full dose of the intervention.¹⁸ We created a covariate for the number of CONNECT visits received before the 3-month assessment (0 for all participants randomized to the standard care group, and number of visits received before the 3-month assessment for participants randomized to the CONNECT group) and divided that by 3. Thus, the variable used to estimate the treatment effect took the value of 0 for a patient who received no visits, 1/3 for a patient who received 1 visit, 2/3 for a patient who received 2 visits, and 1 for a patient who received all 3 planned visits. The interpretation of the regression coefficient for the intensity-adjusted estimate was the treatment effect associated with a full dose (3 visits) of the intervention before the 3-month assessment.

A 2-sided P < .05 was considered to be statistically significant. All statistical analyses used SAS software, version 9.4 (SAS Institute Inc).

Results

Of the 1188 eligible patients, 672 (56.5%) were enrolled. These patients had a mean (SD) age of 69.3 (10.2) years and 360 were women (53.6%), and 312 were men (46.4%) (Table 1). Among these patients, 441 (65.6%) had enrolled caregivers, and 463 (68.9%) completed 3-month assessments.

Table 1. Baseline Characteristics of Enrolled Patients Overall and by Intervention Group.

Characteristic	No. (%)
Characteristic	Full trial population (N = 672)	CONNECT group (n = 336)	Standard care group (n = 336)
Age, mean (SD), y	69.3 (10.2)	68.8 (9.7)	69.8 (10.6)
Sex
Female	360 (53.6)	172 (51.2)	188 (56.0)
Male	312 (46.4)	164 (48.8)	148 (44.0)
Race^a
African American or Black	33 (4.9)	18 (5.4)	15 (4.5)
Asian	5 (0.7)	1 (0.3)	4 (1.2)
White	632 (94.0)	316 (94.0)	316 (94.0)
Refused to answer	2 (0.3)	1 (0.3)	1 (0.3)
Ethnicity^b
Latino/Latina or Hispanic or Latin American	9 (1.3)	4 (1.2)	5 (1.5)
Non-Latino/Latina or Hispanic or Latin American	663 (98.7)	332 (98.8)	331 (98.5)
Educational level
<High school	54 (8.0)	27 (8.0)	27 (8.0)
High school diploma or GED	281 (41.8)	157 (46.7)	124 (36.9)
Some college or college degree	289 (43.0)	130 (38.7)	159 (47.3)
Graduate or professional degree	41 (6.1)	18 (5.4)	23 (6.8)
Refused to answer	7 (1.0)	4 (1.2)	3 (0.9)
Current marital status
Never married	44 (6.5)	18 (5.4)	26 (7.7)
Married	382 (56.8)	184 (54.8)	198 (58.9)
Widowed	132 (19.6)	71 (21.1)	61 (18.2)
Divorced or separated	107 (15.9)	61 (18.2)	46 (13.7)
Refused to answer	2 (0.3)	0	2 (0.6)
Ability to manage on income
Cannot make ends meet	46 (6.8)	26 (7.7)	20 (6.0)
Just manage to get by	226 (33.6)	118 (35.1)	108 (32.1)
Have enough with a little extra	250 (37.2)	129 (38.4)	121 (36.0)
Money is not a problem	108 (16.1)	45 (13.4)	63 (18.8)
Refused to answer	41 (6.1)	17 (5.1)	24 (7.1)
Time since diagnosis with cancer
<1 mo	23 (3.4)	11 (3.3)	12 (3.6)
1-6 mo	174 (25.9)	93 (27.7)	81 (24.1)
>6 mo-1 y	96 (14.3)	52 (15.5)	44 (13.1)
>1-2 y	109 (16.2)	53 (15.8)	56 (16.7)
>2-5 y	131 (19.5)	64 (19.0)	67 (19.9)
>5 y	136 (20.2)	63 (18.8)	73 (21.7)
Refused to answer	1 (0.1)	0	1 (0.3)
Time receiving care from current oncologist
<1 mo	42 (6.3)	23 (6.8)	19 (5.7)
1-6 mo	208 (31.0)	107 (31.8)	101 (30.1)
>6 mo-1 y	114 (17.0)	51 (15.2)	63 (18.8)
>1-2 y	118 (17.6)	64 (19.0)	54 (16.1)
>2-5 y	119 (17.7)	54 (16.1)	65 (19.3)
>5 y	67 (10.0)	35 (10.4)	32 (9.5)
Refused to answer	3 (0.4)	2 (0.6)	1 (0.3)
Currently receiving cancer-directed therapy^c
Chemotherapy	463 (68.9)	230 (68.5)	233 (69.3)
Radiotherapy	33 (4.9)	17 (5.1)	16 (4.8)
Hormonal therapy	14 (2.1)	7 (2.1)	7 (2.1)
Immunotherapy	84 (12.5)	36 (10.7)	48 (14.3)
Cancer type
Genitourinary	73 (10.9)	35 (10.4)	38 (11.3)
Brain	3 (0.4)	2 (0.6)	1 (0.3)
Breast	85 (12.6)	39 (11.6)	46 (13.7)
Gynecologic	28 (4.2)	15 (4.5)	13 (3.9)
Gastrointestinal	131 (19.5)	58 (17.3)	73 (21.7)
Hepatobiliary	79 (11.8)	42 (12.5)	37 (11.0)
Head and neck	13 (1.9)	7 (2.1)	6 (1.8)
Lung	242 (36.0)	130 (38.7)	112 (33.3)
Melanoma	9 (1.3)	6 (1.8)	3 (0.9)
Sarcoma	6 (0.9)	2 (0.6)	4 (1.2)
Other	3 (0.4)	0	3 (0.9)
ECOG Performance Status score
0: Fully active	157 (23.4)	49 (14.6)	108 (32.1)
1: Restricted in physically strenuous activity but ambulatory and able to carry out work of a light or sedentary nature	393 (58.5)	226 (67.3)	167 (49.7)
2: Ambulatory and capable of all self-care but unable to carry out any work activities; up and about >50% of waking hours	122 (18.2)	61 (18.2)	61 (18.2)
Quality of life
FACIT-Pal total score, mean (SD)^d	130 (25.5)	127 (24.9)	133 (25.8)
Symptom burden
ESAS total score, mean (SD)^e	25.2 (16.0)	26.3 (16.0)	24.2 (15.9)
Mood symptoms
HADS, mean (SD)^f
Depression subscale score	5.41 (3.75)	5.70 (3.93)	5.12 (3.56)
Anxiety subscale score	5.78 (3.90)	6.28 (4.07)	5.28 (3.66)

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Abbreviations: CONNECT, Care Management by Oncology Nurses to Address Supportive Care Needs; ECOG, Eastern Cooperative Oncology Group; ESAS, Edmonton Symptom Assessment Scale; FACIT-Pal, Functional Assessment of Chronic Illness Therapy-Palliative care; GED, General Educational Development certificate; HADS, Hospital Anxiety and Depression Scale.

^{^a}

Race and ethnicity information was self-reported by participants.

^{^b}

Participants were asked to answer yes or no to the question, “Are you Latino/Latina or Hispanic or Latin American?” No additional ethnicity categories were offered.

^{^c}

Percentages do not add to 100% because some patients were receiving more than 1 form of cancer-directed therapy and others were not receiving cancer-directed therapy at time of enrollment.

^{^d}

FACIT-Pal score range: 0-184, with higher scores indicating better quality of life.²⁸

^{^e}

ESAS score range: 0-90, with higher scores indicating greater symptom burden.

^{^f}

HADS score range: 0-21, with scores of ≥8 indicating substantial anxiety and depression symptoms.

The most common cancer diagnoses were lung (242 [36.0%]) and gastrointestinal (131 [19.5%]) (Table 1). Patients in the standard care group were more likely than those in the CONNECT group to be fully active (on the basis of ECOG Performance Status score of 0) at baseline (108 [32.1%] vs 49 [14.6%]).

Among patients who were randomized to the CONNECT group and completed the 3-month assessment (n=216), the mean number of visits completed within 3 months was 2.2 (1.0), with 121 patients (56%) receiving all 3 visits (Table 2). Among all 675 intervention visits completed by patients who were randomized to the CONNECT group, the mean (SD) visit length was 40.3 (20.0) minutes for the first visit and 35.4 (18.7) minutes for the subsequent visits. Most visits were conducted in person, on the same day as the patient’s regularly scheduled oncology clinic visit (530 [78.5%]), with the other visits completed in person on a different day (62 [9.2%]) or by telephone (83 [12.3%]). Enrolled caregivers attended 60% of possible visits (231 of 385). Fidelity to key intervention components was acceptable, with a mean (SD) total content score of 87.5% (10.3%) for first visits and 87.8% (11.5%) for subsequent visits (eTable 2 in Supplement 2).

Table 2. Intervention Fidelity Among Patients Who Completed 3-Month Assessments.

No. of CONNECT visits completed within 3 mo	No. (%) (n = 216)
0	23 (10.7)
1	24 (11.1)
2	48 (22.2)
3	121 (56.0)

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Abbreviation: CONNECT, Care Management by Oncology Nurses to Address Supportive Care Needs.

Specialty palliative care visits were rare within the intervention period and did not differ between the CONNECT and standard care groups (2 [0.9%] vs 5 [2.0%]; P = .33). Initiation of hospice care within the intervention period was also rare and did not differ between the CONNECT and standard care groups (8 [3.7%] vs 7 [2.8%]; P = .59). Mortality was not significantly higher in the CONNECT group than the standard care group (80 [23.8%] vs 60 [17.9%]; P = .06).

At 3 months, the mean (SD) quality-of-life score on the FACIT-Pal was 130.7 (28.2) among patients in the CONNECT group and 134.1 (28.1) in the standard care group (adjusted mean difference, 1.20; 95% CI, −2.75 to 5.15; P = .55) (Table 3). The mean (SD) symptom burden (total ESAS score) was 23.2 (16.6) in the CONNECT group and 24.0 (16.1) in the standard care group (adjusted mean difference, −2.64; 95% CI, −5.85 to 0.58; P = .11). Similarly, no differences in mood symptoms were found between the groups at 3 months (HADS depression subscale score: 5.1 [3.4] vs 4.8 [3.7], adjusted mean difference, −0.08 [95% CI, −0.71 to 0.57], P = .82; HADS anxiety subscale score: 5.7 [3.9] vs 5.4 [4.2], adjusted mean difference, −0.31 [95% CI, −0.96 to 0.33], P = .34) (Table 3).

Table 3. Unadjusted Mean Scores and Regression-Estimated Differences in Patient Quality of Life and Symptom Outcomes Between Groups at 3 Months.

Measure			Adjusted mean difference^a	P value	ICC
Measure	CONNECT group	Standard care group	Adjusted mean difference^a	P value	ICC
Quality of life
FACIT-Pal score^b	130.7 (28.2)	134.1 (28.1)	1.20 (−2.75 to 5.15)	.55	0.020
Symptom burden
ESAS score^c	23.2 (16.6)	24.0 (16.1)	−2.64 (−5.85 to 0.58)	.11	0.013
Mood symptoms
HADS^d
Depression subscale score	5.1 (3.4)	4.8 (3.7)	−0.08 (−0.71 to 0.57)	.82	0.007
Anxiety subscale score	5.7 (3.9)	5.4 (4.2)	−0.31 (−0.96 to 0.33)	.34	0.037

Open in a new tab

Abbreviations: CONNECT, Care Management by Oncology Nurses to Address Supportive Care Needs; ESAS, Edmonton Symptom Assessment Scale; FACIT-Pal, Functional Assessment of Chronic Illness Therapy-Palliative care; HADS, Hospital Anxiety and Depression Scale; ICC, intraclass correlation coefficient.

^{^a}

Adjusted mean differences between randomized treatment assignment in 3-month assessments were estimated with linear mixed-effects model, including fixed effects for baseline score, age, cancer type, chemotherapy treatment, Eastern Cooperative Oncology Group Performance Status score, and random effects for clinic; results presented as adjusted mean difference (95% CI) for the CONNECT group vs standard care group.

^{^b}

FACIT-Pal score range: 0-184, with higher scores indicating better quality of life.²⁸

^{^c}

ESAS score range: 0-90, with higher scores indicating greater symptom burden.

^{^d}

HADS score range: 0-21, with scores of ≥8 indicating substantial anxiety and depression symptoms.

Sensitivity analyses performed using multiple imputation and assigning worst-score approaches for patients who missed the 3-month assessment did not substantially alter the estimated intervention effects or conclusions (Table 4). In intensity-adjusted analyses, we found evidence of a larger estimated treatment effect had all patients received the full dose (3 visits) of the CONNECT intervention (total ESAS score: adjusted mean difference, −4.81; 95% CI, −8.29 to −1.33; P = .01) (Table 4).

Table 4. Regression-Estimated Differences in Patient Quality of Life and Symptom Outcomes Between Groups.

Measure	Multiple imputation		Single imputation (assign worst)		Intensity-adjusted analysis
Measure	Adjusted mean difference^a	P value	Adjusted mean difference^b	P value	Adjusted mean difference^c	P value
Quality of life
FACIT-Pal score^d	−0.13 (−6.06 to 5.80)	.97	−6.98 (−16.6 to 2.67)	.16	2.51 (−1.89 to 6.91)	.27
Symptom burden
ESAS score^e	1.08 (−2.28 to 4.45)	.53	2.97 (−3.40 to 9.34)	.36	−4.81 (−8.29 to −1.33)	.01
Mood symptoms
HADS^f
Depression subscale score	−0.09 (−0.77 to 0.59)	.79	0.98 (−0.46 to 2.44)	.18	−0.16 (−0.83 to 0.51)	.63
Anxiety subscale score	−0.00 (−1.00 to 1.01)	.99	0.59 (−0.89 to 2.07)	.44	−0.43 (−1.14 to 0.29)	.24

Open in a new tab

Abbreviations: ESAS, Edmonton Symptom Assessment Scale; FACIT-Pal, Functional Assessment of Chronic Illness Therapy-Palliative care; HADS, Hospital Anxiety and Depression Scale.

^{^a}

Treatment effect was estimated using the same statistical model as the primary results with multiple imputation.

^{^b}

Treatment effect was estimated using the same statistical model as the primary results with single imputation that assigns worst score to patients who did not complete the 3-month assessment.

^{^c}

Treatment effect was estimated using the same statistical model as the primary results with intensity-adjusted approach. Completed number of intervention visits was divided by 3, thereby taking the value of 0 for patients who missed all visits, 1/3 for patients who had 1 of the 3 planned intervention visits, 2/3 for patients who had 2 of the 3 planned intervention visits, and 1 for patients who had all 3 planned intervention visits before the 3-month assessment. The interpretation of regression coefficient was the treatment effect for a patient who received a full dose of intervention.

^{^d}

FACIT-Pal score range: 0-184, with higher scores indicating better quality of life.²⁸

^{^e}

ESAS score range: 0-90, with higher scores indicating greater symptom burden.

^{^f}

HADS score range: 0-21, with scores of ≥8 indicating substantial anxiety and depression symptoms.

Discussion

In this cluster randomized clinical trial, the CONNECT intervention did not improve quality of life (the primary outcome), symptom burden, or symptoms of anxiety and depression at 3 months compared with standard care. To our knowledge, this trial is the largest study to date of a primary palliative care intervention in outpatient oncology. We believe the approach to train and support infusion room nurses who were already part of the clinical team at community oncology practices was unique. We sought to build on findings from previous studies of specialized nursing^7,35 and care management^36,37,38,39 interventions to design a low-cost primary palliative care intervention that leverages existing patient-clinician relationships and has the potential for widespread adoption.

Several possible explanations may be considered for the lack of intervention effect on patient-reported outcomes. First, we may not have delivered a sufficient dose intensity of the intervention to improve outcomes.⁴⁰ We encountered some intervention adherence challenges that were related to visit scheduling, particularly for patients who were not already at the oncology clinic for infusional treatments. This explanation is supported by evidence of a dose effect in the intensity-adjusted analyses we conducted and in other trials.^41,42 More visits over a longer period may be required to improve patient-reported outcomes. However, intensity-adjusted findings must be interpreted with caution given the biases inherent in this observational approach. Additional randomized clinical trials are needed to evaluate the efficacy of more intensive primary palliative care interventions. Second, previous successful palliative care interventions were largely led by physicians or nurse practitioners.^6,7,8,10,43 Although we provided in-depth training to participating nurses and created postvisit check-in protocols with oncologists, more involvement from prescribing clinicians may be required to make an impact on quality of life and symptom burden.

Third, the CONNECT interventionists were infusion room nurses who were also performing other clinical roles (eg, administering chemotherapy). Although we were able to modify nurse schedules to allow for CONNECT visits, many nurses informed us that they felt pulled in multiple directions and sometimes had to shorten CONNECT visits or schedule them for later dates than originally planned because of time constraints.⁴⁴ Given the disconnect between the traditional task-oriented approach of infusion room nurses and the focus on patients’ emotional and psychosocial needs in palliative care, successful primary palliative care delivery in oncology may require larger blocks of protected time and staff who are designated to fulfill primary palliative care roles. Fourth, the patient population may not have had sufficient palliative care needs to derive benefit from the intervention. The baseline FACIT-Pal and ESAS scores in this trial were comparable to the baseline scores in other palliative intervention trials,^6,8,43 but more patients in the standard care group had an ECOG Performance Status score of 0 at baseline, and quality of life and symptom burden did not worsen as much as expected in this group. This score may have caused a negative result, that is, a finding of no effect of the intervention in the setting of an effective intervention.

The findings in this trial highlight the importance of continued efforts to identify successful models of palliative care in oncology that allow for broad dissemination. Expanding patient access to palliative care specialists through telehealth is a promising approach.⁴⁵ Increasing the availability of palliative telehealth services, which may include direct delivery of care (telemedicine) and assistance and resources for primary clinicians who provide palliative care (telementoring), requires an expanded evidence base to support the relative effectiveness of these approaches.^46,47 In response to a surge of unmet palliative care needs during the COVID-19 pandemic, palliative care teams identified and implemented innovative telehealth interventions to rapidly expand access.⁴⁸ Similar innovation is needed to address the ongoing crisis of unmet palliative care needs in advanced cancer.⁴⁹

Limitations

This study has several limitations. First, the participants reflect the largely White, non-Latino/Latina or Hispanic or Latin American population of western Pennsylvania. Findings in this sample may not be generalizable to more racially/ethnically diverse parts of the United States. Second, the study design precluded blinding the participants. We attempted to minimize recruitment bias by informing patients of their randomization group after enrollment. Third, as expected in trials with seriously ill patient populations, the 3-month mortality rate was 20%. Enrolling more patients with an ECOG Performance Status score of 0 in the standard care group may have manifested in a slightly higher mortality in the intervention group. We accounted for this level of attrition in power calculations and conducted preplanned sensitivity analyses to examine the implications of patients dying before the 3-month assessment on the estimated effect of the intervention. Fourth, findings from the intensity-adjusted analyses are potentially confounded by the characteristics of patients who were more likely to receive the full intervention dose. Fifth, despite the rigorous protocol in place to monitor and maintain intervention fidelity, we encountered initial challenges in supporting some nurses who were conducting intervention visits within prespecified time frames, resulting in relatively low adherence to the full intervention dose.

Conclusions

This large, cluster randomized clinical trial found no improvements in patient-reported outcomes from the oncology nurse–led CONNECT intervention compared with standard oncological care. Additional research is needed to identify effective palliative care interventions for patients with advanced cancer who lack access to SPC. Findings from intensity-adjusted analyses are hypothesis generating and suggest that higher dose intensity of palliative care interventions may be beneficial for this patient population.

Supplement 1.

Trial Protocol, Intervention Manual, and CONNECT Study Nurse Training Case Studies

Click here for additional data file.^{(12.2MB, pdf)}

Supplement 2.

eTable 1. Baseline Characteristics of Enrolled Patients vs Declined Patients

eTable 2. Intervention Fidelity Content

Click here for additional data file.^{(124.8KB, pdf)}

Supplement 3.

Data Sharing Statement

Click here for additional data file.^{(17.3KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

Trial Protocol, Intervention Manual, and CONNECT Study Nurse Training Case Studies

Click here for additional data file.^{(12.2MB, pdf)}

Supplement 2.

eTable 1. Baseline Characteristics of Enrolled Patients vs Declined Patients

eTable 2. Intervention Fidelity Content

Click here for additional data file.^{(124.8KB, pdf)}

Supplement 3.

Data Sharing Statement

Click here for additional data file.^{(17.3KB, pdf)}

[ioi210052r1] 1.Downey L, Engelberg RA. Quality-of-life trajectories at the end of life: assessments over time by patients with and without cancer. J Am Geriatr Soc. 2010;58(3):472-479. doi: 10.1111/j.1532-5415.2010.02734.x [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi210052r2] 2.Giesinger JM, Wintner LM, Oberguggenberger AS, et al. Quality of life trajectory in patients with advanced cancer during the last year of life. J Palliat Med. 2011;14(8):904-912. doi: 10.1089/jpm.2011.0086 [DOI] [PubMed] [Google Scholar]

[ioi210052r3] 3.Detmar SB, Aaronson NK, Wever LD, Muller M, Schornagel JH. How are you feeling? who wants to know? patients’ and oncologists’ preferences for discussing health-related quality-of-life issues. J Clin Oncol. 2000;18(18):3295-3301. doi: 10.1200/JCO.2000.18.18.3295 [DOI] [PubMed] [Google Scholar]

[ioi210052r4] 4.Detmar SB, Muller MJ, Wever LD, Schornagel JH, Aaronson NK. The patient-physician relationship: patient-physician communication during outpatient palliative treatment visits: an observational study. JAMA. 2001;285(10):1351-1357. doi: 10.1001/jama.285.10.1351 [DOI] [PubMed] [Google Scholar]

[ioi210052r5] 5.Pollak KI, Arnold RM, Jeffreys AS, et al. Oncologist communication about emotion during visits with patients with advanced cancer. J Clin Oncol. 2007;25(36):5748-5752. doi: 10.1200/JCO.2007.12.4180 [DOI] [PubMed] [Google Scholar]

[ioi210052r6] 6.Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non-small-cell lung cancer. N Engl J Med. 2010;363(8):733-742. doi: 10.1056/NEJMoa1000678 [DOI] [PubMed] [Google Scholar]

[ioi210052r7] 7.Bakitas M, Lyons KD, Hegel MT, et al. Effects of a palliative care intervention on clinical outcomes in patients with advanced cancer: the Project ENABLE II randomized controlled trial. JAMA. 2009;302(7):741-749. doi: 10.1001/jama.2009.1198 [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Effect of an Oncology Nurse–Led Primary Palliative Care Intervention on Patients With Advanced Cancer

Yael Schenker, MD, MAS

Andrew D Althouse, PhD

Margaret Rosenzweig, PhD, CRNP-C, AOCNP

Douglas B White, MD, MAS

Edward Chu, MD, MMS

Kenneth J Smith, MD, MS

Judith M Resick, MSN, MPH, RN

Shane Belin, BS

Seo Young Park, PhD

Thomas J Smith, MD

Marie A Bakitas, DNSc, CRNP

Robert M Arnold, MD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Interventions

Main Outcomes and Measures

Results

Conclusions and Relevance

Trial Registration

Introduction

Methods

Setting and Patient Participants

Randomization and Enrollment

Figure. CONSORT Diagram.

CONNECT Intervention

Standard Care

Data Collection and Patient Outcomes

Statistical Analysis

Results

Table 1. Baseline Characteristics of Enrolled Patients Overall and by Intervention Group.

Table 2. Intervention Fidelity Among Patients Who Completed 3-Month Assessments.

Table 3. Unadjusted Mean Scores and Regression-Estimated Differences in Patient Quality of Life and Symptom Outcomes Between Groups at 3 Months.

Table 4. Regression-Estimated Differences in Patient Quality of Life and Symptom Outcomes Between Groups.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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