NEJM Catalyst, volume 6, issue 3

A Text Message Intervention to Minimize the Time Burden of Cancer Care

Erin M Bange 1, 2
Kerry Q Coughlin 3
Wenrui Li 4, 5
Timothy J. Brown 1, 6
Daniel Ragusano 7, 8
Eesha Balar 9, 10
Dhivya Arasappan 11
Michelle Nnaji 12
Kim Elliot 13
Corey Alban 14
Sindhuja Uppuluri 13
Elizabeth Moriarty 15
Tara Bange 16
Lindsey Zinck 17
David Smith 18
Michael Josephs 19
James J Harrigan 20, 21
Roger B. Cohen 22
Danielle Zubka 23
Roy Rosin 24, 25
Mohan Balachandran 26, 27
Qi Long 28, 29, 30
Andrea Bilger 31
Lynn M. Schuchter 32, 33
Mira Mamtani 34, 35
Lawrence N Shulman 36, 37, 38
Carmen E Guerra 39, 40, 41
Ronac Mamtani 42, 43
Show full list: 28 authors
1
 
Former Medical Oncology Fellow, Abramson Cancer Center, University of Pennsylvania, Philadelphia, USA
2
 
Assistant Professor, Memorial Sloan Kettering Cancer Center, New York, New York, USA
3
 
Project Manager, Abramson Cancer Center, Penn Center for Cancer Care Innovation, University of Pennsylvania, Philadelphia, Pennsylvania, USA
4
 
Former Postdoctoral Researcher, Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
5
 
Assistant Professor, Department of Statistics, University of Connecticut, Storrs, Connecticut, USA
6
 
Assistant Professor of Medicine, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
7
 
Former Project Manager, Abramson Cancer Center, Penn Center for Cancer Care Innovation, University of Pennsylvania, Philadelphia, Pennsylvania, USA
8
 
Medical Student, American University of the Caribbean School of Medicine, Lowlands, Sint Maarten
9
 
Former Research Assistant, Undergraduate Student, University of Pennsylvania, Philadelphia, Pennsylvania, USA
10
 
Medical Student, Georgetown University School of Medicine, Washington, District of Columbia, USA
11
 
Former Research Assistant, TIME Project, University of Pennsylvania, Philadelphia, Pennsylvania, USA
12
 
Medical Sudent, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
13
 
Research Assistant, Undergraduate Student, University of Pennsylvania, Philadelphia, Pennsylvania, USA
14
 
Registered Nurse, Oncology Unit, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
15
 
Registered Nurse, Oncology and Genetics, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
16
 
Researcher, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
17
 
Chief Nursing Officer, Abramson Cancer Center and Cancer Service Line, Penn Medicine, Philadelphia, Pennsylvania, USA
18
 
Informaticist, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
20
 
Former Infectious Diseases Fellow, Hospital of the University of Pennsylvania, USA
21
 
Assistant Professor, Infectious Diseases, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
22
 
Professor of Medicine, Department of Hematology/Oncology, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
23
 
Registered Nurse, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
24
 
Former Chief Innovation Officer, Penn Medicine, Philadelphia, Pennsylvania, USA
25
 
Board Partner, First Round Capital, Philadelphia, Pennsylvania, USA
26
 
Corporate Director, Penn Medicine, Philadelphia, Pennsylvania, USA
27
 
Chief Operating Officer, Way to Health, Penn Medicine Center for Health Care Innovation and the Center for Health Incentives and Behavioral Economics, Philadelphia, Pennsylvania, USA
28
 
Director, Biostatistics and Bioinformatics Core, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
29
 
Associate Director, Penn Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
30
 
Professor of Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
31
 
Director of Operations, University of Pennsylvania, Philadelphia, Pennsylvania, USA
33
 
Madlyn and Leonard Abramson Professor of Clinical Oncology, Division of Hematology Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
34
 
Associate Professor of Clinical Emergency Medicine, Department of Emergency Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
35
 
Associate Residency Program Director, Department of Emergency Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
36
 
Associate Director for Special Projects of the Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
38
 
Professor of Medicine (Hematology/Oncology), Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
39
 
Vice Chair of Diversity and Inclusion, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
40
 
Associate Director of Diversity and Outreach, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
41
 
Ruth C. and Raymond G. Perelman Professor of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
42
 
Section Chief, Genitourinary Cancers, Hematology/Oncology, Penn Medicine, Philadelphia, Pennsylvania, USA
43
 
Associate Professor of Medicine (Hematology/Oncology), Department of Medicine, Abramson Cancer Center, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
Publication typeJournal Article
Publication date2025-02-19
Journal: NEJM Catalyst
scimago Q1
SJR0.654
CiteScore2.8
Impact factor
ISSN26420007
West H.J., Bange E., Chino F.
2023-06-26 citations by CoLab: 5 Abstract  
Telemedicine represents the practical embodiment of patient-centred oncology care, a concept that has become increasingly popular in the past few years. Yet despite the demonstrated benefits of telemedicine, its longitudinal adoption remains limited. Herein we discuss some of the potential challenges that telemedicine faces, as we underutilize this approach relative to its anticipated value.
Gupta A., O'Callaghan C.J., Zhu L., Jonker D.J., Wong R.P., Colwell B., Moore M.J., Karapetis C.S., Tebbutt N.C., Shapiro J.D., Tu D., Booth C.M.
JCO Oncology Practice scimago Q1 wos Q1
2023-06-01 citations by CoLab: 33 Abstract  
PURPOSE: The time spent in pursuing treatments for advanced cancer can be substantial. We have previously proposed a pragmatic and patient-centered metric of these time costs—which we term time toxicity—as any day with physical health care system contact. This includes outpatient visits (eg, bloodwork, scans, etc), emergency department visits, and overnight stays in a health care facility. Herein, we sought to assess time toxicity in a completed randomized controlled trial (RCT). METHODS: We conducted a secondary analysis of the Canadian Cancer Trials Group CO.17 RCT that evaluated weekly cetuximab infusions versus supportive care alone in 572 patients with advanced colorectal cancer. Initial results reported a 6-week improvement in median overall survival (OS) with cetuximab (6.1 v 4.6 months). Subsequent analyses reported that benefit was restricted to patients with K-ras wild-type tumors. We calculated patient-level time toxicity by analyzing trial forms. We considered days without health care contact as home days. We compared medians of time measures across arms and stratified results by K-ras status. RESULTS: In the overall population, median time toxic days were higher in the cetuximab arm (28 v 10, P < .001) although median home days were not statistically different between arms (140 v 121, P = .09). In patients with K-ras–mutated tumors, cetuximab was associated with almost numerically equal home days (114 days v 112 days, P = .571) and higher time toxicity (23 days v 11 days, P < .001). In patients with K-ras wild-type tumors, cetuximab was associated with more home days (186 v 132, P < .001). CONCLUSION: This proof-of-concept feasibility study demonstrates that measures of time toxicity can be extracted through secondary analyses of RCTs. In CO.17, despite an overall OS benefit with cetuximab, home days were statistically similar across arms. Such data can supplement traditional survival end points in RCTs. Further work should refine and validate the measure prospectively. [Media: see text]
Adam R., Duncan L., Maclennan S.J., Locock L.
BMJ Open scimago Q1 wos Q1 Open Access
2023-03-01 citations by CoLab: 9 Abstract  
ObjectivesTreatment burden is the workload of healthcare and the impact this has on the individual. Treatment burden is associated with poorer patient outcomes in several chronic diseases. Illness burden has been extensively studied in cancer, but little is known about treatment burden, particularly in those who have completed primary treatment for cancer. The aim of this study was to investigate treatment burden in survivors of prostate and colorectal cancers and their caregivers.DesignSemistructured interview study. Interviews were analysed using Framework and thematic analysis.SettingParticipants were recruited via general practices in Northeast Scotland.ParticipantsEligible participants were individuals who had been diagnosed with colorectal or prostate cancer without distant metastases within the previous 5 years and their caregivers. Thirty-five patients and six caregivers participated: 22 patients had prostate and 13 had colorectal cancers (six male, seven female).ResultsThe term ‘burden’ did not resonate with most survivors, who expressed gratitude that time invested in cancer care could translate into improved survival. Cancer management was time consuming, but workload reduced over time. Cancer was usually considered as a discrete episode. Individual, disease and health system factors protected against or increased treatment burden. Some factors, such as health service configuration, were potentially modifiable. Multimorbidity contributed most to treatment burden and influenced treatment decisions and engagement with follow-up. The presence of a caregiver protected against treatment burden, but caregivers also experienced burden.ConclusionsIntensive cancer treatment and follow-up regimens do not necessarily lead to perceived burden. A cancer diagnosis serves as a strong motivator to engage in health management, but a careful balance exists between positive perceptions and burden. Treatment burden could lead to poorer cancer outcomes by influencing engagement with and decisions about care. Clinicians should ask about treatment burden and its impact, particularly in those with multimorbidity.Trial registration numberNCT04163068.
Patel K.B., Turner K., Alishahi Tabriz A., Gonzalez B.D., Oswald L.B., Nguyen O.T., Hong Y., Jim H.S., Nichols A.C., Wang X., Robinson E., Naso C., Spiess P.E.
JAMA network open scimago Q1 wos Q1 Open Access
2023-01-10 citations by CoLab: 83 PDF Abstract  
ImportancePatients with cancer typically have greater financial hardships and time costs than individuals without cancer. The COVID-19 pandemic has exacerbated this, while posing substantial challenges to delivering cancer care and resulting in important changes in care-delivery models, including the rapid adoption of telehealth.ObjectiveTo estimate patient travel, time, and cost savings associated with telehealth for cancer care delivery.Design, Setting, and ParticipantsAn economic evaluation of cost savings from completed telehealth visits from April 1, 2020, to June 30, 2021, in a single-institution National Cancer Institute–Designated Comprehensive Cancer Center. All patients aged 18 to 65 years who completed telehealth visits within the designated time frame and had a Florida mailing address documented in their electronic medical record were included in the study cohort. Data were analyzed from April 2020 to June 2021.Main Outcomes and MeasuresThe main outcome was estimated patient cost savings from telehealth, which included 2 components: costs of travel (defined as roundtrip distance saved from car travel) and potential loss of productivity due to the medical visit (defined as loss of income from roundtrip travel plus loss of income from in-person clinic visits). Two different models with a combination of 2 different mileage rates ($0.56 and $0.82 per mile) and census tract–level median hourly wages were used.ResultsThe study included 25 496 telehealth visits with 11 688 patients. There were 4525 (3795 patients) new or established visits and 20 971 (10 049 patients) follow-up visits. Median (IQR) age was 55.0 (46.0-61.0) years among the telehealth visits, with 15 663 visits (61.4%) by women and 18 360 visits (72.0%) by Hispanic non-White patients. According to cost models, the estimated mean (SD) total cost savings ranged from $147.4 ($120.1) at $0.56/mile to $186.1 ($156.9) at $0.82/mile. For new or established visits, the mean (SD) total cost savings per visit ranged from $176.6 ($136.3) at $0.56/mile to $222.8 ($177.4) at $0.82/mile, and for follow-up visits, the mean (SD) total cost savings per visit was $141.1 ($115.3) at $0.56/mile to $178.1 ($150.9) at $0.82/mile.Conclusions and RelevanceIn this economic evaluation, telehealth was associated with savings in patients time and travel costs, which may reduce the financial toxicity of cancer care. Expansion of telehealth oncology services may be an effective strategy to reduce the financial burden among patients with cancer.
Prasad V., Olivier T., Chen E.Y., Haslam A.
Journal of Cancer Policy scimago Q2 wos Q3
2022-12-01 citations by CoLab: 11 Abstract  
Financial costs from cancer treatment are increasingly recognized, but what has historically been underrecognized is the time cost of therapy. We sought to estimate the time burden of anti-cancer drugs approved based on comparisons to best supportive care (BSC), with the assumption that without this drug, a patient could have been treated with observation, home palliative care or hospice services, with minimal time seeking medical care.We searched all FDA approvals (2009 - March 2022) for randomized trials that used BSC as a treatment option for an anti-tumor drug in the metastatic setting and abstracted data on treatment related activities. We then estimated time spent on these activities using previously calculated times.Of the 13 drugs tested against BSC, nine studies demonstrated an improvement in median OS (median 2.1 months). The median monthly time spent for patients in the intervention arm of BSC trials was 15.8 h.Time is a valuable resource for people who have cancer, but especially for patients who may have few to no remaining treatment options, and yet, we found that patients can spend up to 16 h in anti-cancer drug related activities per month.Because survival outcomes are variable for patients being treated in later lines of therapy, time resources are a valuable consideration in the treatment plan.
Bange E.M., Coughlin K., Li W., Moriarty E., Brown T.J., Shulman L.N., Mamtani R.
JAMA network open scimago Q1 wos Q1 Open Access
2022-08-29 citations by CoLab: 4 PDF Abstract  
This cross-sectional study examines whether patients with cancer without symptoms of immune checkpoint inhibitor toxic effects can be accurately identified using a text message–based triage instrument and safely proceed to treatment.
Fundytus A., Sengar M., Lombe D., Hopman W., Jalink M., Gyawali B., Trapani D., Roitberg F., De Vries E.G., Moja L., Ilbawi A., Sullivan R., Booth C.M.
The Lancet Oncology scimago Q1 wos Q1
2021-10-01 citations by CoLab: 98 Abstract  
The WHO Essential Medicines List (EML) identifies priority medicines that are most important to public health. Over time, the EML has included an increasing number of cancer medicines. We aimed to investigate whether the cancer medicines in the EML are aligned with the priority medicines of frontline oncologists worldwide, and the extent to which these medicines are accessible in routine clinical practice.This international, cross-sectional survey was developed by investigators from a range of clinical practice settings across low-income to high-income countries, including members of the WHO Essential Medicines Cancer Working Group. A 28-question electronic survey was developed and disseminated to a global network of oncologists in 89 countries and regions by use of a hierarchical snowball method; each primary contact distributed the survey through their national and regional oncology associations or personal networks. The survey was open from Oct 15 to Dec 7, 2020. Fully qualified physicians who prescribe systemic anticancer therapy to adults were eligible to participate in the survey. The primary question asked respondents to select the ten cancer medicines that would provide the greatest public health benefit to their country; subsequent questions explored availability and cost of cancer medicines. Descriptive statistics were used to compare access to medicines between low-income and lower-middle-income countries, upper-middle-income countries, and high-income countries.87 country-level contacts and two regional networks were invited to participate in the survey; 46 (52%) accepted the invitation and distributed the survey. 1697 respondents opened the survey link; 423 were excluded as they did not answer the primary study question and 326 were excluded because of ineligibility. 948 eligible oncologists from 82 countries completed the survey (165 [17%] in low-income and lower-middle-income countries, 165 [17%] in upper-middle-income countries, and 618 [65%] in high-income countries). The most commonly selected medicines were doxorubicin (by 499 [53%] of 948 respondents), cisplatin (by 470 [50%]), paclitaxel (by 423 [45%]), pembrolizumab (by 414 [44%]), trastuzumab (by 402 [42%]), carboplatin (by 390 [41%]), and 5-fluorouracil (by 386 [41%]). Of the 20 most frequently selected high-priority cancer medicines, 19 (95%) are currently on the WHO EML; 12 (60%) were cytotoxic agents and 13 (65%) were granted US Food and Drug Administration regulatory approval before 2000. The proportion of respondents indicating universal availability of each top 20 medication was 9-54% in low-income and lower-middle-income countries, 13-90% in upper-middle-income countries, and 68-94% in high-income countries. The risk of catastrophic expenditure (spending >40% of total consumption net of spending on food) was more common in low-income and lower-middle-income countries, with 13-68% of respondents indicating a substantial risk of catastrophic expenditures for each of the top 20 medications in lower-middle-income countries versus 2-41% of respondents in upper-middle-income countries and 0-9% in high-income countries.These data demonstrate major barriers in access to core cancer medicines worldwide. These findings challenge the feasibility of adding additional expensive cancer medicines to the EML. There is an urgent need for global and country-level policy action to ensure patients with cancer globally have access to high priority medicines.None.
Kennedy F., Absolom K., Clayton B., Rogers Z., Gordon K., O’Connell Francischetto E., Blazeby J.M., Brown J., Velikova G.
JCO Oncology Practice scimago Q1 wos Q1
2021-03-09 citations by CoLab: 17 Abstract  
PURPOSE: Adverse event (AE) reporting is essential in clinical trials. Clinician interpretation can result in under-reporting; therefore, the value of patient self-reporting has been recognized. The National Cancer Institute has developed a Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) for direct patient AE reporting. A nonrandomized prospective cohort feasibility study aimed to explore the compliance and acceptability of an electronic (Internet or telephone) system for collecting patient self-reported AEs and quality of life (QOL). METHODS: Oncology patients undergoing treatment (chemotherapy, targeted agents, hormone therapy, radiotherapy, and/or surgery) at 2 hospitals were sent automated weekly reminders to complete PRO-CTCAE once a week and QOL (for a maximum of 12 weeks). Patients had to speak/understand English and have access to the Internet or a touch-tone telephone. Primary outcome was compliance (proportion of expected questionnaires), and recruitment rate, attrition, and patient/staff feedback were also explored. RESULTS: Of 520 patients, 249 consented (47.9%)—mean age was 62 years, 51% were male, and 70% were married—and 230 remained on the study at week 12. PRO-CTCAE was completed at 2,301 (74.9%) of 3,074 timepoints and QOL at 749 (79.1%) of 947 timepoints. Individual weekly/once every 4 weeks compliance reduced over time but was more than 60% throughout. Of 230 patients, 106 (46.1%) completed 13 or more PRO-CTCAE, and 136 (59.1%) of 230 patients completed 4 QOL questionnaires. Most were completed on the Internet (82.3%; mean age, 60.8 years), which was quicker, but older patients preferred the telephone option (mean age, 70.0 years). Positive feedback was received from patients and staff. CONCLUSION: Self-reporting of AEs and QOL using an electronic home-based system is feasible and acceptable. Implementation of this approach in cancer clinical trials may improve the precision and accuracy of AE reporting.
Issabakhsh M., Lee S., Kang H.
Health Care Management Science scimago Q1 wos Q2
2020-10-12 citations by CoLab: 18 Abstract  
Infusion centers are experiencing greater demand, resulting in long patient wait times. The duration of chemotherapy treatment sessions often varies, and this uncertainty also contributes to longer patient wait times and to staff overtime, if not managed properly. The impact of such long wait times can be significant for cancer patients due to their physical and emotional vulnerability. In this paper, a mixed integer programming infusion appointment scheduling (IAS) mathematical model is developed based on patient appointment data, obtained from a cancer center of an academic hospital in Central Virginia. This model minimizes the weighted sum of the total wait times of patients, the makespan and the number of beds used through the planning horizon. A mixed integer programming robust slack allocation (RSA) mathematical model is designed to find the optimal patient appointment schedules, considering the fact that infusion time of patients may take longer than expected. Since the models can only handle a small number of patients, a robust scheduling heuristic (RSH) is developed based on the adaptive large neighborhood search (ALNS) to find patient appointments of real size infusion centers. Computational experiments based on real data show the effectiveness of the scheduling models compared to the original scheduling system of the infusion center. Also, both robust approaches (RSA and RSH) are able to find more reliable schedules than their deterministic counterparts when infusion time of patients takes longer than the scheduled infusion time.
Rocque G.B., Williams C.P., Ingram S.A., Azuero A., Mennemeyer S.T., Young Pierce J., Nipp R.D., Reeder‐Hayes K.E., Kenzik K.M.
Cancer Medicine scimago Q1 wos Q2 Open Access
2020-09-21 citations by CoLab: 26 PDF Abstract  
Background Burdens related to time spent receiving cancer care may be substantial for patients with incurable, life-limiting cancers such as metastatic breast cancer (MBC). Estimates of time spent on health care are needed to inform treatment-related decision-making. Methods Estimates of time spent receiving cancer-related health care in the initial 3 months of treatment for patients with MBC were calculated using the following data sources: (a) direct observations from a time-in-motion quality improvement evaluation (process mapping); (b) cross-sectional patient surveys; and (c) administrative claims. Average ambulatory, inpatient, and total health care time were calculated for specific treatments which differed by antineoplastic type and administration method, including fulvestrant (injection, hormonal), letrozole (oral, hormonal), capecitabine (oral, chemotherapy), and paclitaxel (infusion, chemotherapy). Results Average total time spent on health care ranged from 7% to 10% of all days included within the initial 3 months of treatment, depending on treatment. The greatest time contributions were time spent traveling for care and on inpatient services. Time with providers contributed modestly to total care time. Patients receiving infusion/injection treatments, compared with those receiving oral therapy, spent more time in ambulatory care. Health care time was higher for patients receiving chemotherapeutic agents compared to those receiving hormonal agents. Conclusion Time spent traveling and receiving inpatient care represented a substantial burden to patients with MBC, with variation in time by treatment type and administration method.
Bange E.M., Doucette A., Gabriel P.E., Porterfield F., Harrigan J.J., Wang R., Wojcieszynski A.P., Boursi B., Mooney B.I., Reiss K.A., Mamtani R.
JCO Oncology Practice scimago Q1 wos Q1
2020-08-09 citations by CoLab: 41 Abstract  
PURPOSE: The median overall survival (OS) for metastatic pancreatic ductal adenocarcinoma (mPDAC) is < 1 year. Factors that contribute to quality of life during treatment are critical to quantify. One factor—time spent obtaining clinical services—is understudied. We quantified total outpatient time among patients with mPDAC receiving palliative systemic chemotherapy. METHODS: We conducted a retrospective analysis using four patient-level time measures calculated from the medical record of patients with mPDAC receiving 5-fluorouracil infusion, leucovorin, oxaliplatin, and irinotecan; gemcitabine/nab-paclitaxel; or gemcitabine within the University of Pennsylvania Health System between January 1, 2011 and January 15, 2019. These included the total number of health care encounter days (any day with at least one visit) and total visit time. Total visit time represented the time spent receiving care (care time) plus time spent commuting and waiting for care (noncare time). We performed descriptive statistics on these outpatient time metrics and compared the number of encounter days to OS. RESULTS: A total of 362 patients were identified (median age, 65 years; 52% male; 78% white; 62% received gemcitabine plus nab-paclitaxel). Median OS was 230.5 days (7.6 months), with 79% of patients deceased at the end of follow-up. On average, patients had 22 health care encounter days, accounting for 10% of their total days survived. Median visit time was 4.6 hours, of which 2.5 hours was spent commuting or waiting for care. CONCLUSION: On average, patients receiving palliative chemotherapy for mPDAC spend 10% of survival time on outpatient health care. More than half of this time is spent commuting and waiting for care. These findings provide an important snapshot of the patient experience during ambulatory care, and efforts to enhance efficiency of care delivery may be warranted.
Lee A., Shah K., Chino F.
JAMA Oncology scimago Q1 wos Q1
2020-08-01 citations by CoLab: 69 Abstract  
This cross-sectional study reports parking fees at National Cancer Institute–designated cancer treatment centers to assess parking costs for the treatment duration of certain cancers.

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