Validation of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 Summary Score in Patients With Hematologic Malignancies

General population normative values for the EORTC QLQ-C30 by age, sex, and health condition for the French general population

BACKGROUND

General population normative values for the widely used health-related quality of life (HRQoL) measure EORTC QLQ-C30 support the interpretation of trial results and HRQoL of patients in clinical practice. Here, we provide sex-, age- and health condition-specific normative values for the EORTC QLQ-C30 in the French general population.

METHODS

French general population data was collected in an international EORTC project. Online panels with quota samples were used to recruit sex and age groups. Number and type of comorbidities were assessed. Descriptive statistics were used to calculate general population values for each QLQ-C30 scale, separately for sex, age, and presence of one- and more chronic health conditions. A multivariate linear regression model has been developed to allow estimating the effect of sex, age, and the presence for one- and more chronic health conditions on EORTC QLQ-C30 scores. Data was weighted according to United Nation statistics adjusting for the proportion of sex and age groups.

RESULTS

In total, 1001 French respondents were included in our analyses. The weighted mean age was 47.9 years, 514 (51.3%) participants were women, and 497 (52.2%) participants reported at least one health condition. Men reported statistically significant better scores for Emotional Functioning (+9.6 points, p = 0.006) and Fatigue (-7.8 point; p = 0.04); women reported better profiles for Role Functioning (+8.7 points; p = 0.008) and Financial Difficulty (-7.8 points, p = 0.011). According to the regression model, the sex effect was statistically significant in eight scales; the effect of increasing age had a statistically significant effect on seven of the 15 EORTC QLQ-C30 scales. The sex- and age effect varied in its direction across the various scales. The presence of health conditions showed a strong negative effect on all scales.

CONCLUSION

This is the first publication of detailed French normative values for the EORTC QLQ-C30. It aims to support the interpretation of HRQoL profiles in French cancer populations. The strong impact of health conditions on QLQ-C30 scores highlights the importance of considering the impact of comorbidities in cancer patients when interpreting HRQoL data.

Health-related quality of life and quality-adjusted progression free survival for carfilzomib and dexamethasone maintenance following salvage autologous stem-cell transplantation in patients with multiple myeloma: a randomized phase 2 trial by the Nordic Myeloma Study Group

BACKGROUND

Decisions regarding maintenance therapy in patients with multiple myeloma should be based on both treatment efficacy and health-related quality of life (HRQL) consequences. In the CARFI trial, patients with first relapse of multiple myeloma underwent salvage autologous stem cell transplantation (salvage ASCT) before randomization to carfilzomib-dexamethasone maintenance therapy (Kd) or observation. The primary clinical endpoint was time to progression, which was extended by 8 months by Kd. The aim of this paper is to present the all HRQL endpoints of the CARFI trial including the HRQL effect of Kd maintenance therapy relative to observation. The primary HRQL endpoint was assessed by EORTC QLQ-C30 Summary score (QLQ-C30-sum) at 8 months follow-up. A key secondary HRQL endpoint was quality-adjusted progression-free-survival (QAPFS).

METHODS

HRQL was assessed with EORTC QLQ-C30, EORTC QLQ-MY20 and FACT/GOG-Ntx at randomization and every second month during follow-up. HRQL data were analyzed with linear mixed effect models until 8 months follow-up. QAPFS per individual was calculated by multiplying progression-free survival (PFS) by two quality-adjustment metrics, the QLQ-C30-sum and EORTC Quality of Life Utility Measure-Core 10 dimensions (QLU-C10D). The QAPFS per treatment group was estimated with the Kaplan-Meier method. P < 0.05 was used for statistical significance, and a between-group minimal important difference of 10 points was interpreted as clinically relevant for the QLQ-C30-sum.

RESULTS

168 patients were randomized. HRQL questionnaire compliance was 93%. For the QLQ-C30-sum, the difference of 4.62 points (95% confidence interval (CI) -8.9: -0.4, p = 0.032) was not clinically relevant. PFS was 19.3 months for the Kd maintenance group and 16.8 months for the observation group; difference = 2.5 months (95% CI 0.5; 4.5). QAPFS based on the QLQ-C30-sum for the Kd maintenance group was 18.0 months (95% CI 16.4; 19.6) and for the observation group 15.0 months (95% CI 13.5; 16.5); difference = 3.0 months (95% CI 0.8-5.3). QAPFS based on the QLU-C10D for the Kd maintenance group was 17.5 months (95% CI 15.9; 19.2) and 14.0 months (95% CI 12.4; 15.5) for the observation group; difference = 3.5 months (95% CI 1.1-5.9).

CONCLUSIONS

Kd maintenance therapy after salvage ASCT did not adversely affect overall HRQL, but adjustment for HRQL reduced the PFS compared to unadjusted PFS. PFS of maintenance therapy should be quality-adjusted to balance the benefits and HRQL impact.

Evaluating a shared care pathway intervention for people receiving chemotherapy to reduce post-treatment unplanned hospital presentations: a randomised controlled trial

PURPOSE

The aim of this randomised controlled trial (RCT) was to explore whether a community nursing intervention for outpatients receiving systemic therapy reduced unplanned hospital presentations and improved physical and psychosocial health outcomes over the first three cycles of treatment compared to a control group receiving standard care.

METHODS

The number of and reasons for unplanned presentations were obtained for 170 intervention and 176 control group adult patients with solid tumours starting outpatient chemotherapy. Poisson regression was used to compare the number of presentations between the intervention and control groups. Patients self-completed the Hospital Anxiety and Depression Scale, the Cancer Behavior Inventory and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORTC QLQ-C30) at the start of the first four cycles. Linear regression techniques were used to compare quality of life outcomes.

RESULTS

The reduction in unplanned presentations in the intervention group relative to the control group was 12% (95% CI, - 25%, 37%; P = 0.48). At the start of cycle 4, there was no difference in anxiety (difference = 0.47 (95% CI, - 0.28, 1.22; P = 0.22)), depression (difference = 0.57 (95% CI, - 0.18, 1.31; P = 0.13)) or EORTC QLQ-C30 summary score (difference = 0.16 (95% CI, - 2.67, 3.00; P = 0.91)). Scores for self-efficacy as measured by the Cancer Behavior Inventory were higher in the intervention group (difference = 4.3 (95% CI, 0.7, 7.9; P = 0.02)).

CONCLUSION

This RCT did not demonstrate a benefit in reducing unplanned presentations to hospital. The trial identified improved cancer-based self-efficacy in patients receiving the intervention.

TRIAL REGISTRATION

Registered at Australian and New Zealand Clinical Trials Registry: ACTRN12614001113640, registered 21/10/2014.

Financial Toxicity in Patients with Hematologic Malignancies: a Review and Need for Interventions

INTRODUCTION

Financial toxicity is a developing research area to quantify the financial stress experienced by patients and caregivers, as well as the mechanisms by which they manage the costs associated with treatment and the very real harms that this stress can inflict upon cancer care. Patients with blood malignancies experience increased costs associated with their diagnosis due to possible inpatient admissions for treatment, frequent office visits, and even more frequent lab evaluations and testing.

PURPOSE OF REVIEW

Multiple studies have examined the causes and effects of financial toxicity on patient care and outcomes, and there have been several validated tools developed to identify patients experiencing or at risk for financial harm.

DISCUSSION

However, few studies to date have focused on implementing successful interventions to assist in mitigating financial difficulties for patients diagnosed with hematologic malignancies and their families. In this review, we examine the current literature with an emphasis on levels of care, including providers, systems, and policies. Specifically, we discuss published interventions including physician education about treatment costs, financial navigation in cancer centers, and novel institutional multidisciplinary review of patients' financial concerns. We also discuss the urgent need for societal and governmental interventions to lessen financial distress experienced by these highly vulnerable blood cancer patients.

Assessment tools for patient-reported outcomes in multiple myeloma

BACKGROUND

Patients with multiple myeloma experience severe symptom burden. Patient participation in self-reporting is essential as medical staff's assessment of patient symptom severity is often lower than patient self-reporting. This article reviews patient-reported outcome (PRO) assessment tools and their application in the field of multiple myeloma.

RESULTS

The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) is the universal patient-reported outcome assessment tool most frequently used to evaluate the life quality in people with multiple myeloma. Among the specific patient-reported outcome assessment tools, the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Multiple Myeloma Module (EORTC QLQ-MY20), the Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM), and the M.D. Anderson Symptom Inventory-Multiple Myeloma Module (MDASI-MM) are the most widely used, with some scholars using the EORTC QLQ-MY20 as a calibration correlate for scale development. Most current assessment instruments were developed using classical measurement theory methods; future researchers could combine classic theory tests and item response theory to create scientific assessment instruments. In addition, researchers select the appropriate assessment tool based on the purpose of the study. They can translate high-quality assessment tools into different languages and consider applying them more often to assessing multiple myeloma patients. Finally, most existing PROs focus on measuring life quality and symptoms in people with multiple myeloma, with less research on outcomes such as adherence and satisfaction, thus failing to comprehensively evaluate the patient treatment and disease management.

CONCLUSIONS

Research has shown that the field of PROs in multiple myeloma is in an exploratory phase. There is still a need to enrich the content of PROs and develop more high-quality PRO scales for multiple myeloma based on the strengths and weaknesses of existing tools. With the successful advancement of information technology, PROs for people with multiple myeloma could be integrated with electronic information systems, allowing patients to report their health status in real time and doctors to track their condition and adjust their treatment, thereby improving patient outcomes.

Quality of care and quality of life as experienced by patients with advanced cancer of a rare tumour type: results of the multicentre observational eQuiPe study

PURPOSE

Patients with a rare cancer face difficulties during their disease trajectory, such as delayed diagnosis and lack of expert care. However, little is known about their perceived quality of care (QoC) and quality of life (QoL) in the advanced disease stage. We aimed to assess the QoC and QoL as experienced by patients with advanced rare cancers compared to patients with advanced common cancers.

METHODS

In this cross-sectional study, baseline data of patients with advanced cancer from the multicentre, longitudinal, observational eQuipe study were analysed. Multivariable linear regression analyses were conducted to assess differences in experienced QoC (continuity of care, continuity of information, and satisfaction with care) and QoL (functioning, symptoms, overall QoL, and social wellbeing) between advanced rare and common cancer patients.

RESULTS

Of the 1087 included patients, 106 (9.8%) had a rare cancer type. In comparison to patients with advanced common cancers, patients with advanced rare cancers experienced significantly lower continuity of care (77.8 vs. 71.1 respectively, p = 0.011) and social functioning (78.8 vs. 72.6 respectively, p = 0.012). No differences were found regarding continuity of information, satisfaction with care, overall QoL, and social wellbeing.

CONCLUSIONS

Patients with advanced rare cancers experience less continuity of care, and the impact of the disease on social and family life seems higher compared to patients with advanced common cancers.

IMPLICATIONS FOR CANCER SURVIVORS

To enhance the QoC and QoL of patients with advanced rare cancers, supportive care should mainly focus on improving continuity of care and patients' social functioning.

EORTC QLQ-C30 general population normative data for Italy by sex, age and health condition: an analysis of 1,036 individuals

Background

General population normative values for the widely used health-related quality of life (HRQoL) measure, European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire – Core 30 (EORTC QLQ-C30), are available for a range of countries. These are mostly countries in northern Europe. However, there is still a lack of such normative values for southern Europe. Therefore, this study aims to provide sex-, age- and health condition-specific normative values for the general Italian population for the EORTC QLQ-C30.

Material and methods

This study is based on Italian EORTC QLQ-C30 general population data previously collected in an international EORTC project comprising over 15,000 respondents across 15 countries. Recruitment and assessment were carried out via online panels. Quota sampling was used for sex and age groups (18‍–‍39, 40–49, 50–59, 60–69 and ≥ 70 years), separately for each country.

We applied weights to match the age and sex distribution in our sample with UN statistics for Italy. Along with descriptive statistics, linear regression models were estimated to describe the associations of sex, age and health condition with the EORTC QLQ-C30 scores.

Results

A total of 1,036 respondents from Italy were included in our analyses. The weighted mean age was 49.3 years, and 536 (51.7%) participants were female. Having at least one health condition was reported by 60.7% of the participants. Men reported better scores than women on all EORTC QLQ-C30 scales but diarrhoea. While the impact of age differed across scales, older age was overall associated with better HRQoL as shown by the summary score. For all scales, differences were in favour of participants who did not report any health condition, compared to those who reported at least one.

Conclusion

The Italian normative values for the EORTC QLQ-C30 scales support the interpretation of HRQoL profiles in Italian cancer populations. The strong impact of health conditions on EORTC QLQ-C30 scores highlights the importance of adjusting for the impact of comorbidities in cancer patients when interpreting HRQoL data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13211-y.

A systematic review and network meta-analysis of randomized controlled trials on choice of central venous access device for delivery of chemotherapy

OBJECTIVE

Ensuring reliable central venous access with the least complications is vital for cancer patients receiving chemotherapy. A systematic review and network meta-analysis was conducted to compare the safety, quality of life (QoL) and cost effectiveness of different types of central venous access device (CVAD) for patients receiving chemotherapy.

METHODS

PubMed, EMBASE and Cochrane were searched from inception to 20^th August 2021 for randomized controlled trials comparing the various CVADs [non-tunnelled central venous catheter (non-tunnelled catheter), peripherally inserted central venous catheter (PICC), totally implantable ports (PORT), and tunnelled catheter].

RESULTS

A total of 11 eligible RCTs comprising 2585 patients were identified. PORT was associated with lower odds of overall complications, device removal due to complications, thrombotic and mechanical complications compared to PICC [(Odds Ratio (OR) 0.54, 95% CI 0.43 - 0.69), (OR 0.49, 95% CI 0.26 - 0.93), (OR 0.37, 95% CI 0.23 - 0.62) and (OR 0.35, 95% CI 0.13 - 0.95) respectively]. Tunnelled catheter was associated with higher odds of overall complication rate, device removal due to complications and infective complications compared to PORT [(OR 1.68, 95% CI 1.30 - 2.17), (OR 2.52, 95% CI 1.34 - 4.73), (OR 2.11, 95% CI 1.14 - 3.90) respectively]. Ranking probability based on SUCRA values indicated that PORT had the lowest probability of overall complications, removal due to complications, and thrombotic complications.

CONCLUSION

PORT is superior in terms of complications, QoL compared to other CVADs without compromising on cost effectiveness and should be considered the standard of care in patients receiving chemotherapy.

Role of JAK inhibitors in myeloproliferative neoplasms: current point of view and perspectives

Classic Philadelphia-negative myeloproliferative neoplasms (MPN) include polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF), classified as primary (PMF), or secondary to PV or ET. All MPN, regardless of the underlying driver mutation in JAK2/CALR/MPL, are invariably associated with dysregulation of JAK/STAT pathway. The discovery of JAK2V617F point mutation prompted the development of small molecules inhibitors of JAK tyrosine kinases (JAK inhibitors-JAKi). To date, among JAKi, ruxolitinib (RUX) and fedratinib (FEDR) are approved for intermediate and high-risk MF, and RUX is also an option for high-risk PV patients inadequately controlled by or intolerant to hydroxyurea. While not yet registered, pacritinib (PAC) and momelotinib (MMB), proved to be effective particularly in thrombocytopenic and anemic MF patients, respectively. In most cases, JAKi are effective in reducing splenomegaly and alleviating disease-related symptoms. However, almost 50% lose response by three years and dose-dependent toxicities may lead to suboptimal dosing or treatment discontinuation. To date, although not being disease-modifying agents, JAKi represent the therapeutic backbone particularly in MF patient. To optimize therapeutic strategies, many trials with drug combinations of JAKi with novel molecules are ongoing. This review critically discusses the role of JAKi in the modern management of patients with MPN.

Impact of the Extent of Thyroidectomy on Quality of Life in Differentiated Thyroid Cancer Survivors: A Propensity Score Matched Analysis

Purpose

As most thyroid cancer patients survive for more than ten years, it has become increasingly important to understand whether the different surgery types have any effect on the quality of life (QoL) of patients.

Patients and Methods

Using observational data from head and neck surgery at the Sichuan Cancer Hospital in China, three scoring methods – sum scoring, domain-based scoring and IRT-based scoring, were employed to measure the QoL in differentiated thyroid cancer (DTC) patients and a propensity score matched analysis performed to explore the impact of surgery type on QoL as measured by the Treatment of Cancer Quality of Life core Questionnaire version 3.0 (EORTC QLQ-C30) and a disease-specific health-related quality of life questionnaire (THYCA-QoL).

Results

No statistically significant patient QoL differences were found between the two surgery types regardless of which questionnaire was used and which scoring method was used (\documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $${\rm{ATE}} = - 0.400$$ \end{document}, \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $$p = 0.834$$ \end{document} using the EORTC QLQ-C30 and the sum scoring; \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $${\rm{ATE}} = - 0.4491$$ \end{document}, \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $$p = 0.807$$ \end{document} using the EORTC QLQ-C30 and the domain-based scoring; and \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $${\rm{ATE}} = - 0.442$$ \end{document}, \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $$p = 0.114$$ \end{document} using the EORTC QLQ-C30 and the IRT-based scoring; \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $${\rm{ATE}} = - 0.827$$ \end{document}, \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $$p = 0.586$$ \end{document} using the THYCA-QoL and the sum scoring; \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $${\rm{ATE}} = - 1.692$$ \end{document}, \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $$p = 0.406$$ \end{document} using the THYCA-QoL and the domain-based scoring; and \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $${\rm{ATE}} = - 0.032$$ \end{document}, \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $$p = 0.908$$ \end{document} using the THYCA-QoL and the IRT-based scoring).

Conclusion

This study confirmed that the surgery type (hemithyroidectomy or total thyroidectomy) for DTC patients did not appear to influence their general QoL.

Cannabis use among Danish patients with cancer: a cross-sectional survey of sociodemographic traits, quality of life, and patient experiences

PURPOSE

Patients with cancer are using cannabis for self-treatment. The reasons, experienced effects, and prevalence of use are unknown in the European general oncological population.

METHODS

Adult patients with cancer attending outpatient oncology clinics were invited to participate in a cross-sectional survey. The questionnaire consisted of sociodemographic questions, validated scales on quality of life, neuropathy, anxiety and depression as well as questions regarding use of cannabis.

RESULTS

The overall response rate was 83% (2839 patients) and 13% of patients were using or had used cannabis during their treatment. Rate of use was higher in smokers (19% vs 11%, p adjusted 0.002), in patients in active cancer treatment (14% vs 10%, p adjusted = 0.02), and in patients with depression (19% vs 11%, adjusted p = 0.002). Cannabis use was also correlated with lower quality of life (EORTC C30 SumScore mean diff. =  - 7.61, 95% CI = [- 9.69; - 5.53]). In total, 77% of users experienced at least one positive effect of cannabis, 18% experienced no effect, and 5% experienced other effects. At least one side effect was experienced by 33% of users. Management of pain and nausea were the primary reasons for initiating cannabis use (39% for both). Less nausea and better sleep were the most common effects experienced (26% for both). Oils for oral use were the most common route of administration (88%).

CONCLUSION

Cannabis use among patients with cancer is prevalent and correlated with worse quality of life. Patients report using cannabis for symptom management and many experience relief of their symptoms. However, one third of patients experienced side effects.

The GIMEMA-ALLIANCE Digital Health Platform for Patients With Hematologic Malignancies in the COVID-19 Pandemic and Postpandemic Era: Protocol for a Multicenter, Prospective, Observational Study

Background

The COVID-19 pandemic has raised unprecedented challenges in the management of patients with cancer and has increased the demands for digital health tools that, for example, could facilitate remote monitoring of patients. Based on this, the Gruppo Italiano Malattie Ematologiche dell’Adulto (GIMEMA) has recently developed a digital health tool dedicated to patients with hematologic malignancies: the GIMEMA-ALLIANCE platform.

Objective

The main objectives of this web-based platform are to generate relevant data to better understand quality of life, symptoms, and medication adherence during the COVID-19 pandemic and postpandemic era; to develop a prospective real-life registry on outcomes of patients with hematologic cancer, with or without a diagnosis of COVID-19; and to facilitate patient-centered care in routine practice.

Methods

The platform consists of physician- and patient-secure portals and enables electronic patient-reported outcome (ePRO) assessments with real-time graphical presentation to physicians of individual patient symptoms and quality-of-life outcomes. Automated alerts are sent to treating hematologists based on the following predetermined criteria: presence of clinically important problems and symptoms, problems with adherence to therapy, and risk of COVID-19 diagnosis. The platform also allows physicians to set up video consultations. Clinical information regarding disease and treatment as well as clinical and survival outcomes are also prospectively collected.

Results

Recruitment of participants started in December 2020. As of April 2021, a total of 116 patients have been enrolled in this study. Use of this platform may help to improve patient-physician communication and help hematologists in the early recognition of clinically important problems and symptoms of their patients. More than 20 community and university-based hospitals have currently agreed to participate. In addition to patient-reported outcome data, the prospective collection of disease- and treatment-related information, as well as data on possible COVID-19 diagnosis and COVID-19 vaccination, will allow the development of a large database to also identify subgroups of patients at risk of poor outcomes.

Conclusions

Data generated via this platform will help to answer clinically relevant questions for patients with hematologic malignancies during the COVID-19 pandemic and postpandemic era. The use of the GIMEMA-ALLIANCE platform in routine practice may also contribute to enhancing patient-centered care.

Trial Registration

ClinicalTrials.gov NCT04581187; https://clinicaltrials.gov/ct2/show/NCT04581187

International Registered Report Identifier (IRRID)

PRR1-10.2196/25271

Molecular response and quality of life in chronic myeloid leukemia patients treated with intermittent TKIs: First interim analysis of OPTkIMA study

Background

Intermittent treatment with TKIs is an option for the great majority (70%–80%) of CML patients who do not achieve a stable deep molecular response and are not eligible for treatment discontinuation. For these patients, the only alternative is to assume TKI continuously, lifelong.

Methods

The Italian phase III multicentric randomized OPTkIMA study started in 2015, with the aim to evaluate if a progressive de‐escalation of TKIs (imatinib, nilotinib, and dasatinib) is able to maintain the molecular response (MR^3.0) and to improve Health Related Quality of Life (HRQoL).

Results

Up to December 2018, 166/185 (90%) elderly CML patients in stable MR^3.0/MR^4.0 completed the first year of any TKI intermittent schedule 1 month ON and 1 month OFF. The first year probability of maintaining the MR^3.0 was 81% and 23.5% of the patients who lost the molecular response regained the MR^3.0 after resuming TKI continuously. Patients’ HRQoL at baseline was better than that of matched peers from healthy population. Women was the only factor independently associated with worse baseline HRQoL (p > 0.0001). Overall, global HRQoL worsened at 6 (p < 0.001) but returned to the baseline value at 12 months and it was statistically significantly worse in women (p = 0.001).

Conclusions

De‐escalation of any TKI by 1 month ON/OFF schedule maintains the MR^3.0/MR^4.0 in 81% of the patients during the first 12–24 months. No patients progressed to accelerated/blastic phase, all the patients (23.5%) losing MR^3.0 regained the MR^3.0 and none suffered from TKI withdrawn syndrome. The study firstly report on HRQoL in elderly CML patients moving from a continuous daily therapy to a de‐escalated intermittent treatment.

Unique Interplay Between Molecular miR-181b/d Biomarkers and Health Related Quality of Life Score in the Predictive Glioma Models

In the last decade, an increasing amount of research has been conducted analyzing microRNA expression changes in glioma tissue and its expressed exosomes, but there is still sparse information on microRNAs or other biomarkers and their association with patients’ functional/psychological outcomes. In this study, we performed a combinational analysis measuring miR-181b and miR-181d expression levels by quantitative polymerase chain reaction (qPCR), evaluating isocitrate dehydrogenase 1 (IDH1) single nucleotide polymorphism (SNP), and O-6-methylguanine methyltransferase (MGMT) promoter methylation status in 92 post-surgical glioma samples and 64 serum exosomes, including patients’ quality of life evaluation applying European Organization for Research and Treatment of Cancer (EORTC) questionnaire for cancer patients (QLQ-30), EORTC the Brain Cancer-Specific Quality of Life Questionnaire (QLQ-BN20), and the Karnofsky performance status (KPS). The tumoral expression of miR-181b was lower in grade III and glioblastoma, compared to grade II glioma patients (p < 0.05). Additionally, for the first time, we demonstrated the association between miR-181 expression levels and patients’ quality of life. A positive correlation was observed between tumoral miR-181d levels and glioma patients’ functional parameters (p < 0.05), whereas increased exosomal miR-181b levels indicated a worse functional outcome (p < 0.05). Moreover, elevated miR-181b exosomal expression can indicate a significantly shorter post-surgical survival time for glioblastoma multiforme (GBM) patients. In addition, both tumoral and exosomal miR-181 expression levels were related to patients’ functioning and tumor-related symptoms. Our study adds to previous findings by demonstrating the unique interplay between molecular miR-181b/d biomarkers and health related quality of life (HRQOL) score as both variables remained significant in the predictive glioma models.

Experiences with health care and health-related quality of life of patients with hematologic malignancies in Mexico

BACKGROUND

In Mexico, patients with hematologic malignancies (HMs) are characterized by being at high risk and advanced stages at diagnosis and by having a low cure rate; yet information on their experiences with health care and health-related quality of life (HRQL) is scarce. We aimed to evaluate experiences with health care and HRQL of patients with HMs and the association between these patient-reported measures.

METHODS

We conducted a cross-sectional survey in two public oncology hospitals in Mexico City. The study included outpatient cancer patients aged ≥18 years with a diagnosis of leukemia, lymphoma, or multiple myeloma. We used a patient-centered quality of cancer care questionnaire to assess patient experiences with receiving 1) timely care; 2) clear information; 3) information for treatment decision-making; 4) care to address biopsychosocial needs; and 5) respectful and coordinated care. We applied the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) to measure HRQL. We performed a multiple linear regression to evaluate the association between patient-reported experiences (independent variables) and the QLQ-C30 summary score (dependent variable).

RESULTS

Of the 515 participating HM patients, 46.6% had lymphoma, 34% leukemia, and 19.4% multiple myeloma; 70.9% were at advanced stages or at high risk. Additionally, 15.1% had anxiety and 12.8% had depression. Over one third (35.9%) reported receiving clear information, 28.5% timely care, 20.6% information for treatment decision-making, 23.7% care that addressed their biopsychosocial needs, and 31% respectful and coordinated care. The mean QLQ-C30 summary score was 71.9 points. Timely care, clear information, and care that addresses biopsychosocial needs were associated with higher HRQL.

CONCLUSIONS

Health care services for HM patients at public oncology hospitals in Mexico need improvement. Notably, providing timely care, clear information, and care that addresses patients' biopsychosocial needs can increase the likelihood of better HRQL. Health care providers should measure and improve the experiences of HM patients with health care.