Patient-Reported Symptoms and Quality of Life Integrated into Clinical Cancer Care

9 Background: Web-based patient reported outcome (PRO) improved quality of life (QoL), and overall survival (OS) in patients with advanced NSCLC who were treating with specific therapy. Lung Cancer Care application is a mobile application program that provides patients with individually tailored information on patient reported outcome. This study aims to invent a novel mobile application evaluating PRO for Thai NSCLC patients, and to evaluate the validity of mobile application. Methods: Our mobile application-based PRO was designed for monitoring quality of life. The validity of the application was tested following guidelines for translating, and validating a questionnaire. The quality of life score (FACT-L score). After the validated mobile application-based PRO, patients with advanced NSCLC were randomized to use mobile application-based PRO versus routine follow-up. The primary endpoint was quality of life (QoL). Secondary endpoint was OS. Results: Thirty-three patients with advanced NSCLC were enrolled. The mean of FACT-L score at baseline in mobile application-based PRO arm and routine follow up arm was similar (90.08 ± 5.66 vs 91.78 ± 5.26, p-value= 0.82). Patients with mobile application group had more FACT-L score at 3 months than patients with routine follow up arm (106 ± 5.97 vs 99.96 ± 5.74, p-value = 0.07). There was a trend towards increased in different mean of FACT-L score at baseline and 3 months in patients with mobile application compared to patients with routine follow up ( p-value = 0.05). The median follow-up time was 5.43 months, patients with mobile application had longer median OS than patients with routine follow up (4 months vs 2.9 months, p-value = 0.5). Conclusions: Lung Cancer Care application based on self-reported symptoms is a novel electronic device for real-time patient care monitoring. Our study results showed trend towards improved quality of life from using this novel mobile application. However, there was small samples for pilot testing, the relatively large sampling errors may reduce the statistical power needed to validate this tool.

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Financial toxicity in gynecologic cancer survivors and its impact on quality of life.

Journal of Clinical Oncology ◽

10.1200/jco.2020.39.28_suppl.53 ◽

2021 ◽

Vol 39 (28_suppl) ◽

pp. 53-53

Author(s):

Akhil Mehta ◽

Jukes P. Namm ◽

Ellen D'Errico ◽

Eric Lau ◽

Linda Hong ◽

...

Keyword(s):

Quality Of Life ◽

Side Effects ◽

Cancer Survivors ◽

Cancer Care ◽

Uterine Cancer ◽

Gynecologic Cancer ◽

Financial Toxicity ◽

Patient Reported ◽

The Continuum

53 Background: Financial toxicity (FT) is a critical concern for cancer survivors. There is limited data about the relationship between FT throughout the continuum of cancer care, demographics, disease factors, and quality of life (QoL) indicators in gynecologic cancer survivors. Methods: Gynecologic cancer survivors who received treatment from 2015 to 2019 at Loma Linda University Cancer Center were invited to complete an anonymous online survey. A modified version of the comprehensive score for financial toxicity (COST) survey was used to assess FT at baseline and after treatment. The patient-reported outcomes measurement information system (PROMIS) survey was used to assess QoL. Demographic data were summarized using descriptive statistics. Associations between disease factors and FT measured at baseline and after treatment were analyzed using univariable linear regression. Lower COST score coefficients indicate greater FT. Correlations between FT and QoL were evaluated using the Pearson correlation. Results: A total of 252 surveys were sent to gynecologic cancer survivors who met study criteria, of whom 28% responded. Amongst 70 patients included in this analysis, the median age was 64 (IQR 56, 70), 47% were white (n = 33), 20% were unemployed, 22% had a high school or lower level of education, and 50% had an annual income < $60,000. With respect to cancer subtype, 63% had uterine cancer (n = 44), 20% had cervical cancer (n = 14), and 17% had ovarian cancer (n = 12). The mean COST score at baseline and after treatment was 21.2 ± 9.2 and 12.9 ± 7.8, respectively. The following characteristics were associated with significantly greater FT at baseline: Hispanic ethnicity (-5.5; 95% CI: -1 to -10), Black race (-14.4; 95% CI: -3.4 to -25.4), household number > 4 (-6.9; 95% CI: -2.6 to -16.4), Medicare insurance (-6.5; 95% CI: -1.7 to -11.2), and Medicaid insurance (-11.2; 95% CI: -4.3 to -17.9) (p < 0.05). Patients who received combined modality surgery, chemotherapy, and radiation had significantly higher FT (-5.6; 95% CI: -1.3 to -9.8, p < 0.05) compared to those who received single-modality treatment. Likewise, patients with 5 or more treatment-related side effects had significantly higher FT (-6.3; 95% CI -1.13 to -11.4, p < 0.05) compared to those who reported no side effects. During treatment, 24% of patients turned down or skipped treatment, 38% quit their job, and 28% reported family members quit their job. Finally, COST scores measured after treatment correlated positively with physical and mental health (Pearson coefficient 0.57 and 0.56 respectively, p < 0.001). Conclusions: These findings support the need for assessing FT at baseline and throughout the continuum of cancer care to provide individualized assistance to patients facing financial strain. FT affects compliance to treatment which can adversely affect cancer-related outcomes and QoL. Additional policies are needed to address the increasing cost of cancer care.

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Mobile-Health Tool to Improve Care of Patients with Hematological Malignancies

Blood ◽

10.1182/blood-2020-143405 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 35-36

Author(s):

Amit Sanyal ◽

James M. Heun ◽

Jessica Sweeney ◽

Clemens Janssen

Keyword(s):

Quality Of Life ◽

Patient Experience ◽

Cancer Care ◽

Hematological Malignancies ◽

Distress Thermometer ◽

Myelogenous Leukemia ◽

Shortness Of Breath ◽

Symptom Monitoring ◽

Patient Reported

INTRODUCTION Adverse effects are common during treatment of hematological malignancies. Treatment toxicities can impact quality of life [1], impose financial hardship and cause cancer related distress[2]. Symptom monitoring using electronic technology can facilitate early detection of complications[3], reduce symptom burden[4], cost of care[5] and improve survival[6]. Cancer treatment also increases risk of mortality from infections such as coronavirus disease 2019 (COVID-19) and routine screening has been recommended[7]. METHODS We developed an application that periodically delivers toxicity questionnaires to patients during treatment . Based on NCI- PRO-CTCAE™, the questions are delivered through SMS or e-mail. Patient responses crossing prespecified thresholds trigger automated alerts on a dashboard, resulting in additional interventions as needed. Nature and time to intervention is tracked. Patient experience is measured using a Likert-scale and free-text box. Centers for Disease Control recommended COVID-19 screening questions were incorporated. Finally, a distress thermometer for cancer distress screening has been recently added. The app was offered to patients with hematological cancers in a community-based cancer center. RESULTS Since introduction in April 2020, we have enrolled 37 patients. 9 patients had chronic lymphocytic leukemia, 6 diffuse large B cell, 5 mantle cell, 4 Hodgkin's and 3 follicular lymphoma. 2 each had chronic myelogenous, multiple myeloma and Richter's syndrome. 1 each had hairy cell leukemia, acute myelogenous leukemia and T Cell lymphoma. Median age was 64 years (range 24-85). Patient experience has been favorable. On a scale of 1-5, 85.5% rated the experience as 3 or higher. Median patient engagement, calculated by dividing the number of forms completions by number of days enrolled was 34.2% (0.9-66.2 %). Symptom tracker captured 536 responses. Fatigue (153), no symptoms (152), shortness of breath (57), nausea/vomiting, diarrhea (46) and numbness/tingling (28) were the most common response categories. Of 1107 completed check ins, 75 triggered flags. There were 2 hospitalizations for neutropenic fever with the remainder managed as outpatients. Average time between patient generated response and provider intervention was 90.9 minutes. 88% follow-ups were completed within 1 business day. COVID-19 screening module captured 1096 responses. 988 were no symptoms. All positive responses (44 diarrhea, 39 cough, 23 shortness of breath and 2 fever) were false positives. Distress thermometer implemented a week before data cut-off captured 2 responses, 1 in the physical and 1 in the psychological domain. CONCLUSION We demonstrate feasibility of electronic capture of treatment toxicities and offer proof of concept that a mobile app can be used for infection screening. Additionally, the quick response time by care team indicated a high adoption rate. REFERENCES Doorduijn J, B.I., Holt B, Steijaert M, Uyl-de Groot C, Sonneveld P., Self-reported quality of life in elderly patients with aggressive non-Hodgkin's lymphoma treated with CHOP chemotherapy. . European Journal of Hemtology 2005. 75(2): p. 116-123.Troy JD, L.S., Samsa GP, Feliciano J, Richhariya A, LeBlanc TW., Patient-reported distress in Hodgkin lymphoma across the survivorship continuum. Supportive Care Cancer, 2019. 27(7): p. 2453-2462.Stover A M, H.S., Deal A M, Stricker C T, Bennett A V, Carr P M, Jansen J, Kottschade L A, Dueck A C, Basch E M, Methods for alerting clinicians to concerning symptom questionnaire responses during cancer care: Approaches from two randomized trials (STAR, AFT-39 PRO-TECT). Journal of Clinical Oncology 2018. 36(30 supplement): p. 158.Mooney KH, B.S., Wong B, Whisenant M, Donaldson G, Automated home monitoring and management of patient-reported symptoms during chemotherapy: results of the symptom care at home RCT. Cancer Medicine, 2017. 6(3): p. 537-546.Barkley R, S.M.-J., Wang J, Blau S, Page RD, Reducing Cancer Costs Through Symptom Management and Triage Pathways. Journal of Oncology Practice, 2019. 15(2): p. e91-e97.Denis F, B.E., Septans AL, Urban T, Dueck AC, Letellier C., Two-Year Survival Comparing Web-Based Symptom Monitoring vs Routine Surveillance Following Treatment for Lung Cancer. JAMA, 2019. 321(3): p. 306-307.ASCO Special Report: A guide to cancer care delivery during COVID-19 pandemic. 2020, ASCO: Alexandria, VA. Disclosures Janssen: wellbe Inc.: Current Employment.

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Patient related outcomes in cancer patients in Croatia.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.tps6650 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. TPS6650-TPS6650

Author(s):

Dragan Trivanovic ◽

Irena Hrstic ◽

Anuska Budisavljevic ◽

Boris Kopic ◽

Bruno Nincevic

Keyword(s):

Quality Of Life ◽

Cancer Treatment ◽

Cancer Care ◽

Cox Regression ◽

Prospective Trial ◽

Cancer Type ◽

Risk Of Death ◽

Patient Reported ◽

Clinic Visits

TPS6650 Background: Accurate evaluation of symptom intensities is essential for optimal cancer care and improving the quality of life of patients. An inappropriate interpretation of symptoms may lead to treatment outcomes failure, overdose of medication, or may leave the patients undertreated. However, the perception of symptoms can vary between the treating physician and patient. Physicians appear to underestimate the patient symptoms. And this variation in the perception of side effects can lead to wrong assumptions and subsequent treatment changes, affecting treatment effectiveness and quality of life. There is growing interest to enhance symptom monitoring during routine cancer care using patient-reported outcomes, leaving open the question of whether the benefits of systems to reveal self-reports outweigh their added cost. There are several tools for assessment of symptoms in oncology. In cancer treatment clinical trials, the standard source of adverse symptom data is clinician reporting by use of items from PRO-CTCAE, developed by NCI. To address these questions, we conducted a single-center prospective trial to test whether systematic tablet computer-based collection of patient-reported symptoms during chemotherapy treatment, with automated alerts to clinicians for severe adverse events (grade 3-4) will change in questionnaire score at 6 months compared with baseline. Secondary endpoints will include difference in unscheduled clinic visits frequency, and survival. Methods: Patients initiating chemotherapy at General Hospital Pula Oncology Clinic for advanced or metastatic gastrointestinal, lung, breast, genitourinary, or gynecologic cancers will be enrolled in a nonblinded, prospective trial of self-reporting of symptoms, compare with usual care. Patients receiving chemotherapy and their clinicians will be independently asked on the same day to complete 10 symptoms (including fatigue, pain, nausea, vomiting, diarrhea, dysgeusia, appetite, sleep disturbance, fever and hair loss). Participants will remain on study until discontinuation of cancer treatment, withdrawal, or death. All participants will provide written informed consent and followed for up to 28 months or until death. To compare how patient’s vs clinician’s reports relate to clinical events, a time-dependent Cox regression model adjusted for covariates including cancer type, age, sex, and education level will be used to measure associations between reaching particular grade severity thresholds with the risk of death and unscheduled clinic visits. Clinical trial information: 2019-000855-15.

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Association of Physical Morbidity and Health-Related Quality of Life in a Representative Sample of Older German People

European Journal of Health Psychology ◽

10.1027/2512-8442/a000019 ◽

2018 ◽

Vol 25 (4) ◽

pp. 140-151

Author(s):

Markus A. Wirtz ◽

Matthias Morfeld ◽

Elmar Brähler ◽

Andreas Hinz ◽

Heide Glaesmer

Keyword(s):

Quality Of Life ◽

Representative Sample ◽

Short Form ◽

Physical Symptoms ◽

German Population ◽

Health Related Quality ◽

Patient Reported ◽

Related Quality ◽

Health Related

Abstract. The association between health-related quality of life (HRQoL; Short-Form Health Survey-12; SF-12) and patient-reported morbidity-related symptoms measured by the Patient Health Questionnaire-15 (PHQ-15) is analyzed in a representative sample of older people in the general German population. Data from 1,659 people aged 60 to 85 years were obtained. Latent class analysis identified six classes of patients, which optimally categorize clusters of physical symptoms the participants reported: musculoskeletal impairments (39.8%), healthy (25.7%), musculoskeletal and respiratory/cardiac impairments (12.8%), musculoskeletal and respiratory impairments, along with bowel and digestion problems (12.9%), general impairments (4.9%), and general impairments with no bowel and digestion problems (4.8%). The participants’ SF-12 Physical Health Scores (η2 = .39) and their Mental Health Scores (η2 = .28) are highly associated with these latent classes. These associations remain virtually identical after controlling for age. The results provide evidence that profiles of patient-reported physical impairments correspond strongly with reduced HRQoL independently from aging processes.

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