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Special Issue "Palliative Care in Cancer: Recent Advances and Upcoming Trends"

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A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Survivorship and Quality of Life".

Deadline for manuscript submissions: closed (24 November 2023) | Viewed by 6715

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Special Issue Editors

Prof. Dr. Philipp Lenz

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Guest Editor

Institute of Palliative Care, University of Muenster, D-48149 Muenster, Germany
Interests: palliative care; telehealth; symptom control; gastroenterology

Dr. Mitra Tewes
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Co-Guest Editor

Department of Palliative Medicine, West German Cancer Center, University Hospital Essen, 45147 Essen, Germany
Interests: palliative care

Special Issue Information

Dear Colleagues,

The field of palliative care has undergone tremendous advances in recent years, particularly among patients suffering from cancer. However, despite all the existing evidence and excellent research, it remains a relatively young field with numerous challenges and desirable developments. Poignantly, COVID-19 revealed both how important and yet vulnerable the care for patients with incurable diseases continues to be.

It is therefore with great pleasure that I am allowed to specifically focus on innovative approaches in palliative care within the scope of this Special Issue. Thus, thrilling topics may include synergies between “traditional” oncological disciplines and palliative care, novel approaches to the provision of healthcare (e.g., remote care, smart devices, and mobile applications) or the development of more personalized and precise treatments.

I also encourage you to submit projects that aim to lower thresholds between curative and palliative care—even if they cover key topics in palliative care only secondarily.

Prof. Dr. Philipp Lenz
Dr. Mitra Tewes
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

palliative care
palliative medicine
hospice care
symptom control
telehealth
telemedicine
oncology
synergistic effects
personalized medicine
multi-professionalism

Published Papers (5 papers)

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13 pages, 1468 KiB

Open AccessArticle

CT Fluoroscopy-Guided Percutaneous Gastrostomy in the Palliative Management of Advanced and Relapsed Ovarian Cancer: The Charité Experiences and a Review of the Literature

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Cancers 2023, 15(18), 4540; https://doi.org/10.3390/cancers15184540 - 13 Sep 2023

Viewed by 454

Abstract

Peritoneal carcinomatosis-associated malignant bowel obstruction is a common feature that merits more attention in advanced and recurrent ovarian cancer. Decompressive gastrostomy is one of the most preferred methods to palliate distressing symptoms and maintain patients’ quality of life. We retrospectively identified 31 patients with ovarian cancer-associated MBO, who underwent decompressive CT fluoroscopy-guided percutaneous gastrostomy (CT-PG) between September 2015 and April 2023 at our institution. A systematic literature review was conducted for CT-guided gastrostomy in ovarian cancer. Prior to CT-PG, 27 (87%) patients underwent unsuccessful attempts at endoscopic gastrostomy or surgery due to bowel obstruction; a total of 55% had received ≥3 lines of chemotherapy. CT-PG could be successfully inserted in 25 of 31 (81%) patients without grade 4–5 complications. CT-PG insertion was feasible in 76% of patients with previous unsuccessful attempts of endoscopic gastrostomy. A total of 80% of patients with a successful insertion had considerable symptom relief and could tolerate fluid intake. Mean survival after the procedure was 44.4 days. Chemotherapy could be administered in 7 of 25 (28%) patients following the CT-PG insertion. CT-guided percutaneous gastrostomy is a safe procedure that effectively manages intractable symptoms of bowel obstruction in ovarian cancer. This minimally invasive technique should be emphasised as a routine instrument within the palliative management of MBO. Full article

(This article belongs to the Special Issue Palliative Care in Cancer: Recent Advances and Upcoming Trends)

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11 pages, 830 KiB

Open AccessArticle

Does Hospitalist Care Enhance Palliative Care and Reduce Aggressive Treatments for Terminally Ill Patients? A Propensity Score-Matched Study

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Cancers 2023, 15(15), 3976; https://doi.org/10.3390/cancers15153976 - 04 Aug 2023

Viewed by 557

Abstract

Background: Information on the use of palliative care and aggressive treatments for terminally ill patients who receive care from hospitalists is limited. Methods: This three-year, retrospective, case-control study was conducted at an academic medical center in Taiwan. Among 7037 patients who died in the hospital, 41.7% had a primary diagnosis of cancer. A total of 815 deceased patients who received hospitalist care before death were compared with 3260 patients who received non-hospitalist care after matching for age, gender, catastrophic illness, and Charlson comorbidity score. Regression models with generalized estimating equations were performed. Results: Patients who received hospitalist care before death, compared to those who did not, had a higher probability of palliative care consultation (odds ratio (OR) = 3.41, 95% confidence interval (CI): 2.63–4.41), and a lower probability to undergo invasive mechanical ventilation (OR = 0.13, 95% CI: 0.10–0.17), tracheostomy (OR = 0.14, 95% CI: 0.06–0.31), hemodialysis (OR = 0.70, 95% CI: 0.55–0.89), surgery (OR = 0.25, 95% CI: 0.19–0.31), and intensive care unit admission (OR = 0.11, 95% CI: 0.08–0.14). Hospitalist care was associated with reductions in length of stay (coefficient (B) = −0.54, 95% CI: −0.62–−0.46) and daily medical costs. Conclusions: Hospitalist care is associated with an improved palliative consultation rate and reduced life-sustaining treatments before death. Full article

(This article belongs to the Special Issue Palliative Care in Cancer: Recent Advances and Upcoming Trends)

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12 pages, 285 KiB

Open AccessArticle

Electronic Patient-Reported Outcome Measures (ePROMs) Improve the Assessment of Underrated Physical and Psychological Symptom Burden among Oncological Inpatients

Eva Warnecke

Maria Rosa Salvador Comino

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Cancers 2023, 15(11), 3029; https://doi.org/10.3390/cancers15113029 - 01 Jun 2023

Viewed by 1060

Abstract

For advanced cancer inpatients, the established standard for gathering information about symptom burden involves a daily assessment by nursing staff using validated assessments. In contrast, a systematic assessment of patient-reported outcome measures (PROMs) is required, but it is not yet systematically implemented. We hypothesized that current practice results in underrating the severity of patients’ symptom burden. To explore this hypothesis, we have established systematic electronic PROMs (ePROMs) using validated instruments at a major German Comprehensive Cancer Center. In this retrospective, non-interventional study, lasting from September 2021 to February 2022, we analyzed collected data from 230 inpatients. Symptom burden obtained by nursing staff was compared to the data acquired by ePROMs. Differences were detected by performing descriptive analyses, Chi-Square tests, Fisher’s exact, Phi-correlation, Wilcoxon tests, and Cohen’s r. Our analyses pointed out that pain and anxiety especially were significantly underrated by nursing staff. Nursing staff ranked these symptoms as non-existent, whereas patients stated at least mild symptom burden (pain: mean_NRS/epaAC = 0 (no); mean_ePROM = 1 (mild); p < 0.05; r = 0.46; anxiety: mean_epaAC = 0 (no); mean_ePROM = 1 (mild); p < 0.05; r = 0.48). In conclusion, supplementing routine symptom assessment used daily by nursing staff with the systematic, e-health-enabled acquisition of PROMs may improve the quality of supportive and palliative care. Full article

(This article belongs to the Special Issue Palliative Care in Cancer: Recent Advances and Upcoming Trends)

15 pages, 1866 KiB

Open AccessArticle

Telemedical Consultations in Palliative Care: Benefits through Knowledge Exchange and Intercollegiate Collaboration—Findings from the German oVID Project

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Cancers 2023, 15(9), 2512; https://doi.org/10.3390/cancers15092512 - 27 Apr 2023

Cited by 1 | Viewed by 1322

Abstract

(1) Background: As the number of people receiving specialized palliative care (PC) continues to rise, there is a need to ensure the transfer of this expertise from university-based PC departments to primary care hospitals without such in-house access. The present study examines the potential of telemedicine to bridge these gaps. (2) Methods: This is a prospective multi-center feasibility trial. All physicians were appropriately pre-equipped and instructed to conduct telemedical consultations (TCs), which took place within fixed meetings or on-call appointments either related or unrelated to individual patients (allowing TCs also for educational and knowledge exchange purposes). (3) Results: An inquiry for participation was submitted to 11 hospitals, with 5 external hospitals actively cooperating. In the first study section, a total of 57 patient cases were included within 95 patient-related TCs during 80 meetings. Other university disciplines were involved in 21 meetings (26.2%). Therapy adjustments resulted following 25 of 71 affected TCs (35.2%). In 20 cases (21.1%), an on-site consultation at the university hospital was avoided, and in 12 cases (12.6%), a transfer was avoided. Overall, TCs were considered helpful in resolving issues for 97.9% of the cases (n = 93). Yet, technical problems arose in about one-third of all meetings for at least one physician (36.2%; n = 29). Besides, in the second study section, we also conducted 43 meetings between physicians for education and knowledge exchange only. (4) Conclusions: Telemedicine has the potential to transfer university expertise to external hospitals through simple means. It improves collaboration among physicians, may prevent unnecessary transfers or outpatient presentations, and is thus likely to lower costs. Full article

(This article belongs to the Special Issue Palliative Care in Cancer: Recent Advances and Upcoming Trends)

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12 pages, 580 KiB

Open AccessSystematic Review

Applications of Machine Learning in Palliative Care: A Systematic Review

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Cancers 2023, 15(5), 1596; https://doi.org/10.3390/cancers15051596 - 04 Mar 2023

Cited by 3 | Viewed by 1940

Abstract

Objective: To summarize the available literature on using machine learning (ML) for palliative care practice as well as research and to assess the adherence of the published studies to the most important ML best practices. Methods: The MEDLINE database was searched for the use of ML in palliative care practice or research, and the records were screened according to PRISMA guidelines. Results: In total, 22 publications using machine learning for mortality prediction (n = 15), data annotation (n = 5), predicting morbidity under palliative therapy (n = 1), and predicting response to palliative therapy (n = 1) were included. Publications used a variety of supervised or unsupervised models, but mostly tree-based classifiers and neural networks. Two publications had code uploaded to a public repository, and one publication uploaded the dataset. Conclusions: Machine learning in palliative care is mainly used to predict mortality. Similarly to other applications of ML, external test sets and prospective validations are the exception. Full article

(This article belongs to the Special Issue Palliative Care in Cancer: Recent Advances and Upcoming Trends)

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