scholarly journals 300. Long COVID in Cancer Patients: Preponderance of Symptoms in Majority of Patients Over Long Time Period

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S256-S257
Author(s):  
Hiba Dagher ◽  
Alexandre Malek ◽  
Anne-Marie Chaftari ◽  
Ishwaria M Subbiah ◽  
Ying Jiang ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Sleep Disturbances ◽  
Gastrointestinal Symptoms ◽  
Cancer Center ◽  
Cancer Type ◽  
Time Period ◽  
Patient Questionnaires ◽  
Long Time ◽  
Md Anderson ◽  
Definition Of

Abstract Background An increasing number of observational studies have reported the persistence of symptoms following recovery from acute COVID-19 disease. The long-term consequences of COVID-19 are not fully understood and there is no clear consensus on the definition of post-acute sequelae of SARS-CoV-2 infection (PASC). The reported prevalence of PASC widely varies from 10% up to 87%. The purpose of this study is to assess PASC in cancer patients following acute COVID-19 recovery. Methods We assessed cancer patients at MD Anderson Cancer Center who were diagnosed with COVID-19 disease between March 1, 2020 and Sept 1, 2020. Using patient questionnaires and medical chart reviews we followed these patients from March 2020 till May 2021. Patient questionnaires were sent out remotely daily for 14 days after COVID-19 diagnosis then weekly for 3 months, and then monthly thereafter. Chart reviews were conducted for each patient hospital re-admission and emergency department visit. These admissions were classified as either COVID-19 related or non-related. The persistence or emergence of new COVID19-related symptoms were captured at each COVID-19 related admission. Results We included 312 cancer patients with a median age of 57 years (18-86). The majority of patients had solid tumors (75%). Of the 312 patients, 188 (60%) reported long COVID-19 symptoms with a median duration of 7 months and up to 14 months after COVID-19 diagnosis. The most common symptoms reported included fatigue (82%), sleep disturbances (78%), myalgias (67%) and gastrointestinal symptoms (61%), followed by headache, altered smell or taste, dyspnea (47%) and cough (46%). A higher number of females reported a persistence of symptoms compared to males (63% vs 37%; p=0.036). Cancer type, neutropenia, lymphocytopenia, and hospital admission during acute COVID-19 disease were comparable in both groups and did not seem to contribute to a higher number of long-COVID-19 patients in our study group. Conclusion Long-COVID occurs in 60% of cancer patients and may persist up to 14 months after acute illness. The most common symptoms are fatigue, sleep disturbance, myalgia and gastro-intestinal symptoms. Disclosures Fareed Khawaja, MBBS, Eurofins Viracor (Research Grant or Support)

Improving hematology/oncology clinical research recruitment via universal prescreening: The VA Connecticut (VACT) Cancer Center experience.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 79-79
Author(s):  
Jenny Jing Xiang ◽  
Alicia Roy ◽  
Christine Summers ◽  
Monica Delvy ◽  
Jessica Lee O'Donovan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Clinical Trials ◽  
Clinical Research ◽  
Cancer Patients ◽  
Cancer Center ◽  
Cancer Type ◽  
Eligibility Criteria ◽  
Research Recruitment ◽  
Lung Cancer Patients ◽  
Study Enrollment

79 Background: Patient-trial matching is a critical step in clinical research recruitment that requires extensive review of clinical data and trial requirements. Prescreening, defined as identifying potentially eligible patients using select eligibility criteria, may streamline the process and increase study enrollment. We describe the real-world experience of implementing a standardized, universal clinical research prescreening protocol within a VA cancer center and its impact on research enrollment. Methods: An IRB approved prescreening protocol was implemented at the VACT Cancer Center in March 2017. All patients with a suspected or confirmed diagnosis of cancer are identified through tumor boards, oncology consults, and clinic lists. Research coordinators perform chart review and manually enter patient demographics, cancer type and stage, and treatment history into a REDCap (Research Electronic Data Capture) database. All clinical trials and their eligibility criteria are also entered into REDCap and updated regularly. REDCap generates real time lists of potential research studies for each patient based on his/her recorded data. The primary oncologist is alerted to a patient’s potential eligibility prior to upcoming clinic visits and thus can plan to discuss clinical research enrollment as appropriate. Results: From March 2017 to December 2020, a total of 2548 unique patients were prescreened into REDCAP. The mean age was 71.5 years, 97.5% were male, and 15.5% were African American. 32.57 % patients had genitourinary cancer, 17.15% had lung cancer, and 46.15% were undergoing malignancy workup. 1412 patients were potentially eligible after prescreening and 556 patients were ultimately enrolled in studies. The number of patients enrolled on therapeutic clinical trials increased after the implementation of the prescreening protocol (35 in 2017, 64 in 2018, 78 in 2019, and 55 in 2020 despite the COVID19 pandemic). Biorepository study enrollment increased from 8 in 2019 to 15 in 2020. The prescreening protocol also enabled 200 patients to be enrolled onto a lung nodule liquid biopsy study from 2017 to 2019. Our prescreening process captured 98.57% of lung cancer patients entered into the cancer registry during the same time period. Conclusions: Universal prescreening streamlined research recruitment operations and was associated with yearly increases in clinical research enrollment at a VA cancer center. Our protocol identified most new lung cancer patients, suggesting that, at least for this malignancy, potential study patients were not missed. The protocol was integral in our program becoming the top accruing VA site for NCI’s National Clinical Trial Network (NCTN) studies since 2019.

scholarly journals Evaluation of Subjective Sleep Disturbances in Cancer Patients: A Cross-Sectional Study in a Radiotherapy Department

2021 ◽  
Vol 12 ◽  
Author(s):  
Jun Wang ◽  
Bei-Yun Zhou ◽  
Chen-Lu Lian ◽  
Ping Zhou ◽  
Hui-Juan Lin ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Sleep Quality ◽  
Sleep Disturbance ◽  
Sleep Disorders ◽  
Cancer Patients ◽  
Sleep Disturbances ◽  
Cancer Type ◽  
Multivariate Logistic Regression ◽  
Subjective Sleep ◽  
Radiotherapy Department

Background: The factors associated with sleep disturbances in cancer patients remains unclear. This study aimed to explore the prevalence of sleep disorders and predictors associated with sleep disturbance in cancer patients from a radiotherapy department.Methods: Patients with cancers were recruited before the start of radiotherapy from our institution between January 2019 and February 2020. Pittsburgh Sleep Quality Index (PSQI) scale was used to assess sleep quality. Descriptive statistics, Chi-square test, and multivariate logistic regression analysis were used to conduct statistical analysis.Results: A total of 330 eligible patients were included. Of them, 38.3% (n = 127) had the globe PSQI score >7, indicating that they suffered from sleep disorders. Patients with lung cancer (45.2%) were more likely to suffer from sleep disturbance, followed by cervical cancer (43.8%), nasopharyngeal carcinoma (41.7%), esophageal cancer (41.5%), breast cancer (37.7%), and colorectal cancer (30%). With regard to the PSQI components, the mean sleep duration was 8 h, 20.3% (n = 67) of them reported poor subjective sleep quality, 6.1% (n = 20) needed medication to improve sleep, and 53.6% (n = 177) suffered daytime dysfunction. Multivariate logistic regression models showed body mass index (BMI) ≥ 20 kg/m2 [odds ratio (OR) 0.599, 95% confidence interval (CI) 0.329–0.948, P = 0.031] and the receipt of surgery (OR 0.507, 95% CI 0.258–0.996, P = 0.048) were the significant favorable predictors for sleep disturbance, while age, gender, marital status, education level, comorbidity, metastasis status, diagnostic status, and cancer type were not significantly associated with sleep disturbance.Conclusions: Approximately 40% of the cancer patients suffer from sleep disturbance before the start of radiotherapy. Patients with BMI ≥ 20 kg/m2 and receiving surgery are less likely to develop sleep disturbance in comparison with others.

Clinical signs of dying in cancer patients: A prospective longitudinal observational study.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e19528-e19528
Author(s):  
David Hui ◽  
Renata dos Santos ◽  
Kelly L. Kilgore ◽  
Thiago Buosi Silva ◽  
Gary B. Chisholm ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Clinical Signs ◽  
High Specificity ◽  
The United States ◽  
Cancer Center ◽  
Mandibular Movement ◽  
Advanced Cancer Patients ◽  
Palliative Care Units ◽  
Md Anderson ◽  
Prospective Longitudinal

e19528 Background: The fundamental process of dying has not been well characterized. We determined the frequency, onset, accuracy and likelihood ratio (LR) for various clinical signs in dying cancer patients. Methods: We systematically documented 100 signs/symptoms on consecutive advanced cancer patients admitted to palliative care units at MD Anderson Cancer Center (MDA) in the United States and Barretos Cancer Hospital (BCH) in Brazil every 12 hours from admission to death/discharge in 2010/2011. We analyzed the serial data from death backwards using generalized estimating equations for decedents, and calculated the accuracy and LRs for all patients. Results: 203/357 (MDA 52, BCH 151) patients died, and had the following characteristics: average age 58 (range 18-88), female 49%, Caucasian 76%, median admission length 6(Q1-Q3 4-9) days. The average palliative performance scale decreased from 50% to 20% (P<0.001). The frequency of pulselessness of radial artery (PRA), decreased urine output, respiration with mandibular movement (RMM), inability to close eye lids (EL), death rattle, vocal cord grunting, Cheyne Stokes and nasolabial drooping increased as death approached (P<0.001 for all), with high LR+ for impending death (Table 1). Presence of PRA, RMM and EL had a high specificity (100%), positive predictive value (99.4%) and LR+ (13) for death in 3 days. Conclusions: We identified highly specific cardiovascular, respiratory and neuromuscular signs associated with imminent death. [Table: see text]

Implementation of a distress/supportive care screening tool in lung and head and neck cancer clinic.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e21646-e21646
Author(s):  
Mary Pasquinelli ◽  
Sandra Obilade ◽  
David Rosenberg ◽  
Zane Deliu ◽  
Aakash Shah ◽  
...  
Keyword(s):  
Supportive Care ◽  
Cancer Patients ◽  
Neck Cancer ◽  
Screening Tool ◽  
Supportive Care Needs ◽  
Cancer Center ◽  
Head Neck Cancer ◽  
Cancer Type ◽  
Care Needs ◽  
Head Neck

e21646 Background: Identifying and addressing depression, anxiety, and supportive care needs in cancer patients is an emerging standard of care. The Coleman Foundation “Patient Screening Questions for Supportive Care” tool was used with demographic and diagnostic data to investigate the relationships between screening scores. Methods: Lung/head/neck cancer patients at the University of Illinois Cancer Center were screened using the Coleman Foundation tool. This screening tool identified needs in several categories including Patient Health Questionnaire 4 (PHQ-4) scores; practical, family/caregiver, nutritional, treatment, physical, and spiritual/faith/religious concerns; levels of pain, fatigue, physical activity to quantitatively assess patient distress/supportive care needs. Scores were compared with age, sex, race/ethnicity, insurance, cancer type, and cancer stage. Linear regression was used for statistical analysis. Results: We performed initial screening on 164 lung/head/neck patients ages 36-88 (mean 61), with stages IA to IVC (May 2016 to Jan. 2017). Our findings are summarized in below. We found a 1oeffect that racial/ethnic minority status was significantly correlated with higher scores. We found that lung cancer was correlated with higher screening scores than head & neck on initial screen. Medicare insurance was correlated with significantly lower screening scores. Conclusions: Patients with lung/head/neck cancer have significant needs and concerns that go beyond merely treating their cancer. Our findings show that certain demographic groups have especially high burdens in some specific dimensions and that these specific concerns may be predicted based on diagnostic and demographic information. Thus, these findings serve to inform providers as to where and how to focus supportive care for these patient populations. [Table: see text]

Mortality within 30 days of immunotherapy (checkpoint inhibitors) in metastatic cancer patients treated at Australian tertiary cancer center.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 6600-6600
Author(s):  
Hiren A. Mandaliya ◽  
Sang Kim ◽  
Gaik Tin Quah ◽  
Sandy Tun Min ◽  
James Carlton ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Advanced Cancer ◽  
Checkpoint Inhibitors ◽  
Metastatic Cancer ◽  
Univariate Analysis ◽  
Cell Cancer ◽  
Small Sample ◽  
Cancer Center ◽  
Published Data ◽  
Cancer Type

6600 Background: Cancer treatment has evolved rapidly since the advent of immunotherapy (checkpoint inhibitors). As compared to chemotherapy, immunotherapy is associated with a more favourable but distinct side effect profile. Mortality within 30 days of chemotherapy in cancer patients has been accepted as a clinical indicator of preventable harm and used as an auditing tool for clinical practice and improving quality of life. This should be investigated in the current era of immunotherapy, as it has been the standard treatment for advanced melanoma, lung cancer, renal cell cancer and others. Methods: We conducted a retrospective study on patients with advanced cancer treated with immunotherapy and died within 30 days of treatment. Clinical data on patients treated with immunotherapy at Calvary Mater Newcastle between 2006 and 2018 was collected. Data were compared with 30-day mortality statistics of chemotherapy. Results: A total of 601 metastatic cancer patients received immunotherapy agents (Pembrolizumab, Nivolumab, Ipilimumab, Atezolizumab, Tislelizumab and MSB0011359C) on 5022 occasions. Seventy-six (12.6%) patients died within 30 days of receiving immunotherapy. Median age was 68 years (35-90). Melanoma was the most prevalent cancer type (63%) followed by lung (20%). Forty-seven (47%) of patients received immunotherapy as first-line treatment and 39% as second-line. Patients died within 30 days received an average 2 (1-16) immunotherapy doses. A quarter of patients had ECOG 3 and ECOG 4 before last dose. Majority of deaths were related to disease (86%). Nearly 80% of patients died in hospital. One patient died due to treatment-related pneumonitis. In univariate analysis, there was no association between mortality and patients’ demographic variables such as age, sex, BMI, cancer type, ECOG performance status, immunotherapy agent and prior treatment. Conclusions: To our knowledge, this is the first ever real-world data on 30-day mortality after immunotherapy in advanced cancer. Thirty-day mortality rates were comparable to published data on patients treated with chemotherapy. Results emphasise significance of careful selection of advanced cancer patient for immunotherapy. Due to small sample size, the power to detect a significant association between patients demographics and survival is reduced.

Prognostic significance of the “surprise” question in cancer patients

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 9588-9588
Author(s):  
A. H. Moss ◽  
J. R. Lunney ◽  
S. Culp ◽  
M. Auber ◽  
S. Kurian ◽  
...  
Keyword(s):  
Palliative Care ◽  
End Of Life ◽  
Cancer Patients ◽  
Prognostic Significance ◽  
Cox Proportional Hazards ◽  
Cancer Center ◽  
P Value ◽  
Cancer Type ◽  
Patient Death ◽  
Surprise Question

9588 Background: In patients with advanced cancer, failure to accurately estimate and communicate prognoses can lead to overly aggressive care at the end of life with less attention to important palliative care issues such as pain and symptom management and patients’ values and goals for care. The “surprise” question—would I be surprised if this patient died in the next year?—has been recognized as an innovation to improve end-of-life care in the primary care population by identifying patients with a poor prognosis who are appropriate for palliative care. It has not been previously tested in cancer patients. The purposes of this study were to determine the feasibility and outcomes of the use of the “surprise” question in a cancer center population. Methods: Between July and November 2007, oncologists prospectively classified consecutive breast, lung, and colon cancer patients being seen at the Mary Babb Randolph Cancer Center of West Virginia University into “Yes” and “No” groups based on the surprise question. Patients were followed and their status at the end of one year-alive or dead-was determined along with patient demographics, type of cancer, and stage at presentation. A multivariate Cox proportional hazards regression analysis was used to identify variables associated with patient death. Results: Oncologists classified 826 of 853 prospective patients (97%), with 131 (16%) classified into the “No” group and 695 (84%) into the “Yes” group. At the end of the year, 71 patients had died; 41% of the “No” patients compared to 3% of the “Yes” patients (P <.001). The surprise question ‘No‘ response was more predictive of patient death than stage of cancer, cancer type, or age (hazard ratio 7.53, P value <.001). The “Yes” patients lived longer than the “No” patients (359.8±32.8 days versus 270±131.5 days, P <.001). The sensitivity of the surprise question “No” response was 75% and the specificity was 90%. Conclusions: We conclude that the surprise question is a simple, feasible, and effective tool to identify cancer patients with the worst prognoses who should receive the highest priority for palliative care interventions, particularly advance care planning. No significant financial relationships to disclose.

Involving clinic patients in systematic symptom reporting to improve cancer care: Exploring prevalence of sleep disturbances (SD) and fatigue (FAT).

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 68-68
Author(s):  
Margaret Irwin ◽  
Catherine Brown ◽  
Ashlee Vennettilli ◽  
Lawson Eng ◽  
Aein Zarrin ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Sleep Disturbances ◽  
Healthcare Providers ◽  
Severity Index ◽  
Symptom Reporting ◽  
Care Plan ◽  
Systematic Evaluation ◽  
Cancer Center ◽  
Falling Asleep ◽  
Patient Reported

68 Background: SD and FAT occur in 30-50% of cancer patients. Patient-reported outcome measure surveys are avenues through which healthcare providers (HCP) can receive symptom-related clinically relevant information directly from patients, and engage them in their own care plan. By asking patients to report symptoms rapidly through tablet/computer-based technology, HCPs can involve patients in the delivery of care. Methods: In a pilot study evaluating utility of systematic symptom reporting, 336 adult cancer patients across all stages and disease sites who were attending outpatient cancer clinics at Princess Margaret Cancer Centre (PMCC) (Toronto, Canada) completed electronic tablet-administered secure surveys on SD (Insomnia Severity Index) and FAT patterns (FACT-fatigue). These tools measured both symptom severity and interference with function. Results: With a median age of 59 (19-91) years, 55% female, across a broad distribution of cancer sites, 56% of our sample reported moderate to very severe (MTVS) SD over the last 7 days: 31% had MTVS difficulty falling asleep; 43% had MTVS difficulties staying asleep; 36% had MTVS problems waking up too early. While 62% who had MTVS SD were not distressed by their SD, 95% who were distressed by their SD met the criteria of MTVS SD. 78% of patients had any level of FAT over the last 7 days, with 40% reporting MTVS FAT. While 40% who had MTVS FAT were still able to perform their usual activities, 67% of patients who were not able to do their usual activities had MTVS FAT. Conclusions: Across all stages and disease sites of cancer patients at PMCC, the prevalence of SD and FAT was both high. Severity and interference with function by FAT and SD were often distinct and non-overlapping. Involving patients in the systematic evaluation of symptoms, particularly using newer tablet-based technology within the clinic, was feasible. Through the use of patient reported electronic applications, patients could easily and systemically report their symptoms in real-time. FAT management has always been a high priority at our institution. However, based on our results, a cancer center-wide self-management plan is being considered for SD.

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