Identify Cancer Patients Research Articles

Investigation of the relationship between lymphocyte subsets and intestinal parasites

We analyzed the peripheral blood lymphocyte subsets of cancer patients infected with intestinal parasites, with an aim to find out the relationship between the levels of different types of lymphocytes with the prognosis of patients. 201 cancer patients aged 18 and over were included. Stool samples of the patients were examined using native-lugol, trichrome, modified trichrome (Weber's Trichrome stain), and modified Ziehl-Neelsen staining methods. Microsporidia and Cryptosporidium parvum were investigated at the genus and species levels using PCR. Lymphocyte subsets were determined by flow cytometry in blood samples. One or more parasite species were detected in 115 (56.7%) patients. The most common parasite species were Microsporidia, Blastocystis and Entamoeba coli, respectively. The frequency of parasites was high in patients with low lymphocyte percentage, CD3+ T cell and CD3+ CD4+ T (Th) cell levels in blood samples studied by flow cytometry. Microsporidia infection was significantly higher in patients with low lymphocyte percentage and Th cell levels. Similarly, C. parvum infection was found to be significantly higher in patients with low T lymphocyte percentage and Th cell level. Finally, Blastocystis infection was significantly higher in patients with low lymphocyte percentage and CD4/CD8 ratio higher than 1. The decrease in lymphocyte percentage, CD3+ T cell and Th cell count, and low CD4/CD8 ratio in cancer patients increase the frequency of intestinal parasitic infections. Based on these results, lymphocyte subsets may help identify cancer patients at high risk of opportunistic parasites. We suggest that opportunistic parasitic infections affecting the clinical course of the disease should be considered by clinicians during the follow-up and treatment of patients.

Predicting Unplanned Hospitalization Among Patients Receiving Definitive Radiation

<h3>Purpose/Objective(s)</h3> A small fraction of cancer patients receiving definitive radiation experience unplanned hospitalizations related to treatment, which potentially leads to substantial morbidity or mortality. Identifying patients at high risk of unplanned hospitalizations could help with risk stratification, and potentially help inform future interventions aimed at improving patient outcomes. This study evaluated the predictive capacity of a machine learning prediction algorithm to identify unplanned hospitalizations and intensive care unit (ICU) visits among a large cohort of patients undergoing definitive radiation therapy. <h3>Materials/Methods</h3> We identified cancer patients undergoing definitive radiation therapy from the Veterans Health Administration (VHA) between 2000 and 2017. We used an extreme gradient boosting model to separately predict the risk of unplanned hospitalization and ICU admission within 30 days of completion of radiation treatment. Model covariates included patient demographics, cancer stage and subtype, and treatment information including previous chemotherapy and surgery. The data were split 75%/25% into training/testing datasets. We constructed the model with training data and evaluated performance within the test data using area under the curve (AUC), with an AUC of 1.0 indicating perfect prediction. <h3>Results</h3> We identified 60,804 cancer patients from 14 tumor subtypes receiving definitive radiation therapy, of which 936 (1.5%) experienced an unplanned hospitalization with 113 (0.19%) escalated to the ICU. Our final predictive model included 30 features, which contained 10 demographic variables and 20 tumor or treatment characteristics. The predictive models achieved an AUC of 0.82 and 0.79 for predicting unplanned hospitalization and ICU visit, respectively. Emergency department visits prior to radiation treatment was identified as the most important associated feature for predicting both unplanned hospitalizations and ICU visits. Other features including tumor subtype, Charlson comorbidity score, previous chemotherapy, and biologic effective dose were also important predictors in the final models. <h3>Conclusion</h3> This study demonstrates that a machine learning model can help provide a robust prediction of unplanned hospitalizations and ICU admission among cancer patients receiving definitive radiation. Machine learning prediction models show promise in helping to identify patients at risk of severe adverse outcomes, though additional validation is needed as well as research studying how to effectively implement these tools into practice.

Identification of Remaining Life Expectancy Less Than Two Weeks by C-Reactive Protein/Albumin Ratio, Prognostic Nutritional Index, Fibrosis-4 Index, and Albumin-Bilirubin Score in Terminal Cancer Patients.

Background: Accurate prognosis in terminal cancer patients is useful to improve their quality of life and also to decide the cessation of fluid administration. Nonetheless, few prognostic indicators are available for prediction of such a short-term life expectancy. Objectives: The present study aimed at evaluating the efficacy of C-reactive protein (CRP)/albumin (CRP/Alb) ratio, prognostic nutritional index (PNI), fibrosis-4 (FIB-4) index, and albumin-bilirubin (ALBI) score in identifying terminal cancer patients who have a life expectancy less than two weeks. Design: Retrospective study. Setting/Subjects: Of 483 patients who died between April 2019 and March 2020 at a single center in Japan, 102 who met the inclusion criteria were enrolled in this study. Measurements: CRP/Alb, PNI, FIB-4, and ALBI were calculated from the laboratory data collected 1-13, 14-27, 28-83, and 168-365 days before death and subjected to statistical analyses. Results: CRP/Alb, PNI, FIB-4, and ALBI values were significantly associated with the time before death during terminal 365 days. CRP/Alb ≥4.4, PNI <30, FIB-4 ≥ 9.4, and ALBI ≥ -1.26 were significantly associated with the transition from the first half to the second half of terminal four weeks. Of those prognostic indicators, three and four combinations provided significantly reliable estimation of a life expectancy less than two weeks. Conclusions: CRP/Alb, PNI, FIB-4, ALBI, and their combinations are considered to help identify cancer patients who have a life expectancy less than two weeks, which is useful to make appropriate end-stage treatment decisions, for example, cessation of artificial hydration therapy.

Prognostic factors at admission on patients with cancer and COVID-19: Analysis of HOPE registry data

BackgroundPrevious works seem to agree in the higher mortality of cancer patients with COVID-19. Identifying potential prognostic factors upon admission could help identify patients with a poor prognosis. MethodsWe aimed to explore the characteristics and evolution of COVID-19 cancer patients admitted to hospital in a multicenter international registry (HOPE COVID-19).Our primary objective is to define those characteristics that allow us to identify cancer patients with a worse prognosis (mortality within 30 days after the diagnosis of COVID-19). Results5838 patients have been collected in this registry, of whom 770 had cancer among their antecedents. In hospital mortality reached 258 patients (33.51%). The median was 75 years (65–82). Regarding the distribution by sex, 34.55% of the patients (266/770) were women.The distribution by type of cancer: genitourinary 238/745 (31.95%), digestive 124/745 (16.54%), hematologic 95/745 (12.75%).In multivariate regression analysis, factors that are independently associated with mortality at admission are: renal impairment (OR 3.45, CI 97.5% 1.85–6.58), heart disease (2.32, 1.47–3.66), liver disease (4.69, 1.94–11.62), partial dependence (2.41, 1.34–4.33), total dependence (7.21, 2.60–21.82), fatigue (1.84, 1.16–2.93), arthromialgias (0.45, 0.26–0.78), SatO2<92% (4.58, 2.97–7.17), elevated LDH (2.61, 1.51–4.69) and abnormal decreased Blood Pressure (3.57, 1.81–7.15). Analitical parameters are also significant altered. ConclusionIn patients with cancer from the HOPE registry, 30-day mortality from any cause is high and is associated with easily identifiable clinical factors upon arrival at the hospital. Identifying these patients can help initiate more intensive treatments from the start and evaluate the prognosis of these patients.

Serious illness conversation and end of life care utilization at an academic medical center.

29 Background: Hospice has been associated with improved quality of life for patients, cost savings, and reduction in caregiver-grief-related depression. While cancer patients make up a plurality of hospice utilizers nationally, many patients are only on hospice for a limited period (in Medicare patients, a median of 18 days). Studies suggest engaging cancer patients to discuss goals and priorities using the Serious Illness Conversation (SIC) Guide has a positive impact on prognostic understanding and end-of-life planning. More frequent utilization of SICs may prompt earlier enrollment of oncology patients in hospice when appropriate. Methods: We identified cancer patients enrolled in hospice at the Abramson Cancer Center at Penn Presbyterian Medical Center from 2019-2020 after all providers received SIC training. Patient demographics, cancer diagnosis, type of hospice (home versus inpatient), SIC usage, palliative care referral patterns and time on hospice were abstracted. Results: 104 patients were enrolled in hospice during the study period. The majority of patients were female (51%). 45% were Caucasian, and 31% were African American. The most common cancer diagnoses were thoracic (52%) and gastrointestinal (32%) malignancies. 85 patients (82%) were enrolled on home hospice and 19 patients (18%) inpatient hospice. Palliative care usage included 50 inpatient and 24 outpatient consultations; 30 patients (29%) in the cohort never utilized palliative care. 52 (50%) of patients did not have a SIC. 47% (40 patients) enrolled in home hospice had an SIC while 63% (12 patients) on inpatient hospice had an SIC. The median time interval between a patient’s SIC conversation and hospice enrollment was longer in home hospice patients (74 days) compared to inpatient hospice (33 days). Patients on home hospice spent an average of 44 days on hospice versus 2 days in the inpatient setting. Conclusions: Half of the patients at Penn Presbyterian Medical Center enrolled in hospice during the study period did not have an SIC, and 29% did not see palliative care prior to starting hospice. The median time from SIC initiation to hospice enrollment was significantly longer for patients on home hospice compared to inpatient hospice suggesting a need for earlier SIC interventions. Patients enrolled in inpatient hospice spent a considerably shorter period of time on hospice also underscoring the importance of earlier end of life planning. Our findings indicate a need for additional interventions to facilitate earlier SIC conversations in the outpatient setting and a demand for increased palliative care access.

COVID-19 infection in the cancer population: a study of emergency department imaging utilization and findings.

PurposeTo analyze emergency department (ED) computerized tomography (CT) utilization in cancer patients with coronavirus disease 2019 (COVID-19).MethodsA retrospective chart review was performed to identify cancer patients who received COVID-19 diagnosis within the single healthcare system and presented to the ED within 30 days of COVID-19 positive date between May 1 and December 31, 2020.ResultsIn our 61 patients, the mean age was 72.5 years old, with 34% of patients (n = 21) on active cancer therapy and 66% (n = 40) on surveillance only. Most patients (n = 53) received their COVID-19 diagnosis within the ED, with 8 patients diagnosed prior to initial ED visit. The most common CT studies ordered within the ED were CT chest (n = 25), CT abdomen/pelvis (A/P) (n = 20), CT head (n = 8), and CT chest/abdomen/pelvis (C/A/P) (n = 7). COVID-19 findings were present on 33 scans, findings of worsening malignancy on 12 scans, and non-COVID non-cancer findings on 9 scans. Significant differences in CT severity score (p = 0.0001), indication for hospitalization (p = 0.026), length of hospitalization (p = 0.004), interventions (remdesivir, mechanical ventilation, and vasopressor support) while hospitalized (p < 0.05), and mortality (p = 0.042) were found between the prior diagnosis and ED diagnosis groups. No such differences were found between the active treatment and surveillance groups.ConclusionED CT imaging findings in patients with cancer and COVID-19 are predominantly related to COVID-19 infection, rather than cancer history or anti-cancer therapy status.

Introduction to the third issue of Aging and Cancer

Dr. Samuel Waxman has dedicated his career to the treatment of cancer patients and to cancer research. While he led an extraordinarily successful medical practice for 45 years, he understood very early that knowledge is power and that without research, cancer treatment would remain highly toxic. His passion for research is best illustrated by the creation of the Samuel Waxman Cancer Research Foundation (SWCRF) in 1976. The SWCRF currently funds a network of 30 researchers across the world and raised over $100 million for cancer research. To this day, the passion of this remarkable physician-scientist has only become stronger. His most recent goal is to understand the link between cancer and aging. While cancer is known to be an age-related disease, surprisingly, little research focuses on how and why cancer is more frequent in older individuals. Dr. Waxman has, therefore, not only established collaboration between his foundation and the National Institute of Aging to specifically fund research projects aimed at understanding the link between aging and cancer but also teamed up with Wiley Publishing to launch this new journal in 2020. In this third edition of Aging and Cancer, three articles from SWCRF investigators were selected to illustrate the range of questions and approaches needed to cover the complexity of the link between aging and cancer. The first article by our group (Jenkins et al. Are the estrogen receptor and SIRT3 axes of the mitochondrial UPR key regulators of breast cancer sub-type determination according to age? Aging and Cancer, 2021. https://doi.org/10.1002/aac2.12035) focuses on the counterintuitive observation that breast cancer in post-menopausal women, which have much lower levels of circulating estrogen due to the cessation of ovarian function at menopause, tends to develop cancers that show elevated expression of the estrogen receptor. The second article by Edward Evans and SWCRF investigator James DeGregori (Evans et al. Cells with Cancer-associated Mutations Overtake Our Tissues as We Age. Aging and Cancer, 2021) uses an unbiased approach of a meta-analysis of published sequencing data on normal tissues to determine how many cancer-associated mutations are present in cancer-free individuals with age. They present evidence that these mutations are actually found at high frequency across tissues. This finding immediately raises the question as to why some individuals go on to develop cancer, while others do not. In direct line with the Evans study, the third article by SWCRF-associated investigator Paolo Boffetta and colleagues (Franchi et al. Developing a multimorbidity prognostic score in elderly patients with solid cancer using administrative databases from Italy. Aging and Cancer, 2021) takes an epidemiological approach to interrogate multiple conditions and their association with Cancer Multimorbidity Score (CMS). Their study suggests that the CMS may be used clinically to identify cancer patients at higher risk of mortality within 5 years. Finally, a fourth article by SWCRF investigator Ruibao Ren and colleagues (Li et al. The potential of cord blood to replenish young immune cells against cancer. Aging and Cancer. 2021;2:36–44. https://doi.org/10.1002/aac2.12032) was published in the second issue of Aging and Cancer and focused on whether interventions aimed at improving healthy aging can reduce the risk of cancer with age. In this review, the authors summarized the most recent findings regarding the potential therapies leveraging cord blood to replenish young immune cells in elderly cancer patients. Collectively, these perspective, review, and research articles provide a brief overview of some of the research perform by scientists funded by the SWCRF in the emerging field of Aging and Cancer. SWCRF funding recipient since 2002.

Identification of canine circulating miRNAs as tumor biospecific markers using Next-Generation Sequencing and Q-RT-PCR

Delay in cancer diagnosis often results in metastasis and an inability to successfully treat the tumor. The use of broadly cancer-specific biomarkers at an early stage may improve cancer treatment and staging. This study has explored circulatory exosomal miRNAs as potential diagnostic biomarkers to identify cancer patients. Secretory exosomal miRNAs were isolated from 13 canine cancer cell lines (lymphoma, mast cell tumor, histiocytic cell line, osteosarcoma, melanoma, and breast tumor) and were sequenced by Next-Generation sequencing (NGS). We have identified 6 miRNAs (cfa-miR-9, -1841, −1306, −345, −132, and −26b) by NGS that were elevated in all cancer cell types. The miRNAs identified by NGS were then examined by Q-RT-PCR. The PCR data demonstrated similar expression patterns to those seen with NGS but provided fold differences that were much lower than those seen for NGS. Cfa-miR-9 was found to be the most consistently elevated miRNA in NGS and PCR, making it the most likely miRNA to prove diagnostic. In this study, we have demonstrated that it is possible to identify exosomal miRNAs with elevated secretion across multiple tumor types that could be used as circulatory diagnostic biomarkers for liquid biopsy in the future.

Khorana score stratification and incidence of venous thromboembolism among women with ovarian cancer receiving neoadjuvant chemotherapy

<h3>Objectives:</h3> In the AVERT and CASSINI randomized trials, a Khorana score (KS) ≥ 2 was used to identify cancer patients with a high risk of venous thromboembolism (VTE) who may benefit from thromboprophylaxis during chemotherapy. We aimed to describe the relationship between KS and incidence of venous thromboembolism among women with ovarian cancer (OC) receiving neoadjuvant chemotherapy (NACT). <h3>Methods:</h3> The study cohort included patients receiving NACT for primary ovarian, fallopian tube, or peritoneal cancer from January 2000 to June 2018 from two academic institutions. KS immediately preceding NACT was calculated using established parameters (prechemotherapy platelet count ≥350, hemoglobin <10 or use of red blood cell growth factors, leukocyte count >11, and BMI ≥35). Fisher exact test was used to compare the primary outcomes of incidence of VTE at diagnosis or during NACT for patients with KS of 1 versus KS ≥2. <h3>Results:</h3> From a total NACT cohort of 277, there were 241 patients included in the analysis for whom a pre-NACT KS could be calculated. Overall, 25% had a KS of 1 (n=62), 44% KS of 2 (n=107), 26% KS of 3 (n=63), and 3.7% KS of 4 (n=9). Twenty- five patients presented with a VTE at the time of cancer diagnosis, including 6 of the 62 women with a KS of 1 (9.7%) and 19 among the 179 women with a KS of ≥2 (10%). An additional 15 patients experienced a VTE during NACT, including two with a KS of 1 (3%) and 13 with a KS ≥2 (7%). The rates of VTE between these two strata (KS of 1 versus KS ≥2) were not significantly different for either VTE at diagnosis or during NACT (<i>p=1.0</i> [95% CI 0.28-2.5] and <i>p=0.37</i> [95% CI 0.04-1.97], respectively). <h3>Conclusions:</h3> A KS of ≥2 has previously been used as a risk stratification tool for consideration of thromboprophylaxis among cancer patients receiving chemotherapy. However, women receiving NACT for OC with a KS of 1 or KS ≥2 in this cohort had similar rates of VTE both at diagnosis and during NACT. Although larger sample sizes are needed, these preliminary results suggest that all women receiving NACT for OC are at high risk for VTE and consideration of thromboprophylaxis may be warranted irrespective of Khorana score.

Establishment of CORONET: COVID-19 Risk in Oncology Evaluation Tool to Identify Cancer Patients at Low Versus High Risk of Severe Complications of COVID-19 Infection Upon Presentation to Hospital

Establishment of CORONET: COVID-19 Risk in Oncology Evaluation Tool to Identify Cancer Patients at Low Versus High Risk of Severe Complications of COVID-19 Infection Upon Presentation to Hospital

Cost-effectiveness of precision diagnostic testing for precision medicine approaches against non-small-cell lung cancer: A systematic review.

Precision diagnostic testing (PDT) employs appropriate biomarkers to identify cancer patients that may optimally respond to precision medicine (PM) approaches, such as treatments with targeted agents and immuno‐oncology drugs. To date, there are no published systematic appraisals evaluating the cost‐effectiveness of PDT in non‐small‐cell lung cancer (NSCLC). To address this gap, we conducted Preferred Reporting Items for Systematic Reviews and Meta‐Analyses searches for the years 2009–2019. Consolidated Health Economic Evaluation Reporting Standards were employed to screen, assess and extract data. Employing base costs, life years gained or quality‐adjusted life years, as well as willingness‐to‐pay (WTP) threshold for each country, net monetary benefit was calculated to determine cost‐effectiveness of each intervention. Thirty‐seven studies (50%) were included for analysis; a further 37 (50%) were excluded, having failed population‐, intervention‐, comparator‐, outcomes‐ and study‐design criteria. Within the 37 studies included, we defined 64 scenarios. Eleven scenarios compared PDT‐guided PM with non‐guided therapy [epidermal growth factor receptor (EGFR), n = 5; programmed death‐ligand 1 (PD‐L1), n = 6]. Twenty‐eight scenarios compared PDT‐guided PM with chemotherapy alone (anaplastic lymphoma kinase, n = 3; EGFR, n = 17; PD‐L1, n = 8). Twenty‐five scenarios compared PDT‐guided PM with chemotherapy alone, while varying the PDT approach. Thirty‐four scenarios (53%) were cost‐effective, 28 (44%) were not cost‐effective, and two were marginal, dependent on their country’s WTP threshold. When PDT‐guided therapy was compared with a therapy‐for‐all patients approach, all scenarios (100%) proved cost‐effective. Seven of 37 studies had been structured appropriately to assess PDT‐PM cost‐effectiveness. Within these seven studies, all evaluated scenarios were cost‐effective. However, 81% of studies had been poorly designed. Our systematic analysis implies that more robust health economic evaluation could help identify additional approaches towards PDT cost‐effectiveness, underpinning value‐based care and enhanced outcomes for patients with NSCLC.

Appendectomy and Cholecystectomy Outcomes for Pediatric Cancer Patients with Leukopenia: A NSQIP-Pediatric Study

BackgroundChildren with cancer often develop leukopenia which may impair wound healing and increase surgical complication rates. When leukopenic children with cancer develop an acute surgical condition, the optimal management strategy remains unclear. This study examined the effect of preoperative leukopenia on postoperative outcomes in children with cancer who underwent an appendectomy or cholecystectomy. MethodsWe retrospectively identified cancer patients undergoing an appendectomy or cholecystectomy from the National Surgical Quality Improvement Program-Pediatric database from 2012-2018. Demographics and perioperative characteristics were compared by leukopenia status (WBC <4 vs. ≥4 × 10^3/mL). Postoperative length of stay (LOS) and 30-day composite complications, including infections, reoperations, and readmissions, were analyzed for each procedure using multivariate regression. ResultsThere were 227 children who underwent an appendectomy and 101 children who underwent a cholecystectomy. Leukopenia was seen in 93 (41.0%) appendectomy and 57 (56.4%) cholecystectomy cases. Nineteen (8.4%) appendectomy patients and six (5.9%) cholecystectomy patients developed a postoperative complication. The median postoperative LOS was 2 days (IQR 1-6 days) for appendectomy and 1 day (IQR 1-2.5 days) for cholecystectomy cases. After multivariate analyses, leukopenia was not associated with increased postoperative complications after an appendectomy (OR 0.55, P = 0.36) or cholecystectomy (OR 0.39, P = 0.37). There was no significant difference in postoperative LOS based on leukopenia status for children who underwent an appendectomy (P = 0.82) or cholecystectomy (P = 0.37). ConclusionIn pediatric cancer patients, leukopenia was not associated with increased short-term postoperative complications or longer postoperative LOS after either an appendectomy or cholecystectomy. These results support that operative management can be performed safely in pediatric appendicitis and cholecystitis in leukopenic cancer patients.

Abstract 381: Elevated PARP7 expression in select cancers identifies a target population for RBN-2397 therapy

Abstract PARP7 (TIPARP) is a monoPARP which catalyzes the transfer of single units of ADP-ribose onto substrates to change their function. Its expression is upregulated during cellular stress, including viral infection or through the activation of the aryl hydrocarbon receptor after exposure to cigarette smoke. We and others have shown that PARP7 activity suppresses the Type I interferon (IFN) response following activation by cytosolic nucleic acid sensing pathways. RBN-2397 is a first-in class PARP7 inhibitor, which induces cancer cell autonomous and immune stimulatory effects in preclinical models through enhanced Type I IFN signaling in cancer cells. Here we describe the presence of PARP7 genomic amplification with corresponding increased mRNA expression across select cancers. Elevated PARP7 expression or amplification may identify cancer patients that could derive benefit from treatment with RBN-2397. In characterizing PARP7 copy number and mRNA expression from The Cancer Genome Atlas (TCGA) database, we found the presence of PARP7 copy number amplification in a subset of tumor types, particularly those of squamous histology, as well as ovarian cancer that corresponded to higher mRNA expression levels. High PARP7 expression correlated with poor survival in squamous cancers, while it had no effect on survival in ovarian cancer. Interestingly, tumor types with high PARP7 expression also expressed higher levels of baseline interferon stimulated genes (ISGs). This parallels our findings that cancer cell lines with higher ISGs at baseline are more responsive to PARP7 inhibition. To explore PARP7 copy number variations (CNVs) in advanced cancer patients, we queried the FoundationCore® (Foundation Medicine, Inc) database. Similar to TCGA, squamous cancers as well as ovarian, breast, and pancreatic ductal adenocarcinoma (PDAC) were among the tumor types with PARP7 amplifications. Moreover, PARP7 was found to be amplified both on the background of chromosome 3q arm-level amplifications as well as focally. Congruent to our analysis of PARP7 amplifications, we evaluated PARP7 mRNA expression in both squamous and non-squamous non-small cell lung carcinoma (NSCLC), breast cancer, and PDAC primary tumor samples. Using a validated RNAscope ISH probe set, we analyzed over 1,000 patient samples and found that PARP7 was more highly expressed in tumor cells relative to corresponding normal tissues. Overall, there were varying levels of PARP7 expression across samples with higher expression levels of PARP7 in tumor cells, compared to stroma, across all cancers examined. Our analyses describing the presence of PARP7 amplifications as well as high expression levels in several tumor types including NSCLC, breast, and PDAC provides evidence for the therapeutic relevance of PARP7 inhibition and highlights potential patient selection strategies to identify those patients more likely to benefit from RBN-2397 treatment. Citation Format: Jodie Wong, Kristy Kuplast-Barr, Ryan P. Abo, Anupriya S. Kulkarni, Linda T. Nieman, Azfar Neyaz, Katherine H. Xu, Radwa Sharaf, Lee A. Albacker, David T. Ting, Heike Keilhack, Kristen A. McEachern. Elevated PARP7 expression in select cancers identifies a target population for RBN-2397 therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 381.

Abstract 701: The acute phase response identifies cancer patients with adverse outcomes from SARS-CoV-2 infection as quantified by the OnCovid Inflammatory Score

Abstract Background. Systemic inflammation is a pathogenic mechanism shared by infection and cancer. Mortality from Covid-19 is strongly linked to systemic cytokine excess. We investigated systemic inflammation as a driver of Covid-19 severity in patients with Covid-19 and cancer. Methods. Between 27/02 and 23/06/2020, OnCovid retrospectively accrued 1,318 consecutive European cancer patients with Covid-19. Patients with myeloma, leukemia, or insufficient data were excluded. The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), prognostic nutritional index (PNI), modified Glasgow prognostic score (mGPS), and prognostic index (PI) were evaluated for their prognostic potential, with the NLR, PLR, and PNI risk stratifications dichotomized around median values, and the pre-established risk categorizations from literature utilized for the mGPS and PI. Results. 1,071 eligible patients were randomly assorted into a training set (TS, n=529) and validation set (VS, n=542) matched for age (67.9±13.3 TS, 68.5±13.5 VS), presence of &amp;gt;1 comorbidity (52.1% TS, 49.8% VS), development of &amp;gt;1 Covid-19 complication (27% TS, 25.9% VS), and active malignancy at Covid-19 diagnosis (66.7% TS, 61.6% VS). Among all 1,071 patients, deceased patients tended to categorize into poor risk groups for the NLR, PNI, mGPS, and PI (P&amp;lt;0.0001). Recovered patients fully normalised NLR, PNI, and mGPS to pre-Covid-19 diagnosis levels (P&amp;lt;0.01). In the TS, higher mortality rates were associated with NLR&amp;gt;6 (44.6% vs 28%, P&amp;lt;0.0001), PNI&amp;lt;40 (46.6% vs 20.9%, P&amp;lt;0.0001), mGPS (50.6% for mGPS2 vs 30.4% and 11.4% for mGPS1 and 0, P&amp;lt;0.0001), and PI (50% for PI2 vs 40% for PI1 and 9.1% for PI0, P&amp;lt;0.0001). Findings were confirmed in the VS (P&amp;lt;0.001 for all comparisons). Patients in poor risk categories had shorter median overall survival [OS] (NLR&amp;gt;6 30 days 95%CI 1-63, PNI&amp;lt;40 23 days 95%CI 10-35, mGPS2 20 days 95%CI 8-32, PI2 23 days 95%CI 1-56) compared to patients in good risk categories, for whom median OS was not reached (P&amp;lt;0.001 for all comparisons). The PLR was not associated with survival. Analyses of survival in the VS confirmed the NLR (P&amp;lt;0.0001), PNI (P&amp;lt;0.0001), PI (P&amp;lt;0.01), and mGPS (P&amp;lt;0.001) as predictors of survival. In a multivariable Cox regression model including all inflammatory indices, the PNI was the only independent predictor in both TS and VS analysis (TS hazard ratio [HR] 1.97, 95%CI 1.19-3.26, P=0.008; VS HR 2.48, 95%CI 1.47-4.20, P=0.001). Estimates were adjusted for sex, age, comorbid burden, active malignancy, and receipt of anti-cancer therapy within 4 weeks of Covid-19 diagnosis. Conclusion. Systemic inflammation drives mortality from Covid-19. Hypoalbuminemia and lymphocytopenia as measured by the PNI are the most accurate predictors of outcome and enable repurposing of the PNI as the OnCovid Inflammatory Score (OIS) as a readily available biomarker of severity. Citation Format: Gino M. Dettorre, Saoirse Dolly, Angela Loizidou, John Chester, Amanda Jackson, Uma Mukherjee, Alberto Zambelli, Juan Aguilar-Company, Mark Bower, Christopher C. Sng, Ramon Salazar, Alexia Bertuzzi, Joan Brunet, Ricard Mesia, Ailsa Sita-Lumsden, Elia Seguí, Federica Biello, Daniele Generali, Salvatore Grisanti, Pavetha Seeva, Gianpiero Rizzo, Michela Libertini, Antonio Maconi, Charlotte Moss, Josep Tabernero, Beth Russell, Nadia Harbeck, Bruno Vincenzi, Rossella Bertulli, Diego Ottaviani, Raquel Liñan, Andrea Marrari, M. Carmen Carmona-García, Neha Chopra, Carlo Tondini, Oriol Mirallas, Valeria Tovazzi, Vittoria Fotia, Claudia Andrea Cruz, Nadia Saoudi-Gonzalez, Eudald Felip, Ariadna Roqué, Alvin J. Lee, Thomas Newsom-Davis, Andrea Patriarca, Lorenza Rimassa, Armando Santoro, Alessandra Gennari, Nikolaos Diamantis, David J. Pinato. The acute phase response identifies cancer patients with adverse outcomes from SARS-CoV-2 infection as quantified by the OnCovid Inflammatory Score [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 701.

Diagnostic codes of cancer in Sk\xe5ne healthcare register: a validation study using individual-level data in southern Sweden

BackgroundThe Swedish healthcare is decentralised to 21 regions. Detailed information on all delivered care in the southernmost region, Skåne, is prospectively collected in the Skåne Healthcare Register (SHR). The data is updated daily and hence a good source for epidemiological studies. However, the diagnostic codes used to identify cancer patients in SHR have not yet been validated.MethodsWe conducted a validation study including 1,473,204 residents in Skåne region during 2005–2014, with at least one physical consultation in SHR. Newly diagnosed cancer from the Swedish Cancer Register was considered the ‘gold standard’ reference. We estimated the positive predictive value (PPV), sensitivity, and area under the curve (AUC) of a cancer diagnosis based on SHR by level of consultation, for any cancer, and for different cancer types.ResultsThere were 61,693 cancers from the Swedish Cancer Register, and 87,650 cancers from SHR. The PPV of SHR-based diagnosis of any cancer was 63.76% (95% confidence interval (CI): 63.44–64.08%) with a sensitivity of 90.58% (95% CI: 90.35–90.81%). The AUC was 0.94, for any cancer. The measures of PPV, sensitivity and AUC varied across levels of care and were higher in specialized care than in primary care. The highest PPV was observed for specialist inpatient care in SHR (89.17, 95% CI 88.89–89.45%) whereas the highest sensitivity was observed for specialized outpatient care in SHR (86.39, 95%CI 86.12–86.66%). Robust validity was noted among most cancers, except for cancers of soft tissues, central nervous system and eye, and endocrine glands.ConclusionsOur study supports that SHR is a valid and robust healthcare register for cancer diagnosis, with varying validities across levels of care and cancer types. This makes SHR a useful data source for cancer epidemiological studies, especially because the data covers the entire cancer care pathways without time lags for further linkage.

Use of Treatment-Focused Tumor Sequencing to Screen for Germline Cancer Predisposition

Next-generation sequencing assays are capable of identifying cancer patients eligible for targeted therapies and can also detect germline variants associated with increased cancer susceptibility. However, these capabilities have yet to be routinely harmonized in a single assay because of challenges with accurately identifying germline variants from tumor-only data. We have developed the Oncology and Hereditary Cancer Program targeted capture panel, which uses tumor tissue to simultaneously screen for both clinically actionable solid tumor variants and germline variants across 45 genes. Validation using 14 tumor specimens, composed of patient samples and cell lines analyzed in triplicate, demonstrated high coverage with sensitive and specific identification of single-nucleotide variants and small insertions and deletions. Average coverage across all targets remained >2000× in 198 additional patient tumor samples. Analysis of 55 formalin-fixed, paraffin-embedded tumor samples for the detection of known germline variants within a subset of cancer-predisposition genes, including one multiexon deletion, yielded a 100% detection rate, demonstrating that germline variants can be reliably detected in tumor samples using a single panel. Combining targetable somatic and actionable germline variants into a single tumor tissue assayrepresents a streamlined approach that can inform treatment for patients with advanced cancers as well as identify those with potential germline variants who are eligible for confirmatory testing, but would not otherwise have been identified.

Prevalence of Venous Thromboembolism in Cancer Patients in the Emergency Department and Associated Healthcare Resource Utilization and Expenditure in the United States

BackgroundVenous thromboembolism (VTE) is one of the leading causes of morbidity and mortality in cancer patients. We investigated VTE prevalence in cancer patients in the emergency department (ED) setting, associated utilization of health care resources and costs.MethodsThe Agency for Healthcare Research and Quality sponsored Nationwide Emergency Department Sample (NEDS) database was used to identify cancer patients and ED utilizations in 2006-12. The NEDS database captures 20% of US ED visits. Cancer types (solid tumor, lymphoma, leukemia, multiple myeloma) and acute venous thromboembolism [VTE, which includes deep vein thrombosis (DVT) and/or pulmonary embolism (PE)] were identified by ICD-9 codes. CPT procedure codes were used to identify any use of computed tomography pulmonary angiography (CTPA), CT chest with contrast (CTC), duplex ultrasound of the veins (DUS), or ventilation-perfusion (VQ) scan. Descriptive statistics were used to present the VTE prevalence, use of imaging study, admission rates and costs incurred. Chi-square test were used to compare death/admission rate and chi-square test for trend was used for trend analysis. Multivariable logistic regression modeling was used to explore the association between VTE diagnosis and hospital admission or death during hospital course after baseline characteristics adjustment.ResultsThere were 6,330,322 ED visits by cancer patients in our study, which represented 3.2 % of total ED visits from 2006-2012 in the NEDS database. Over the study period, 1.6% of patients received either CTPA, CTC, DUS, or V/Q scan during their ED visits (CTPA: 0.56%; CTC: 0.47%; DUS: 0.62%; V/Q: 0.02%). The use of imaging studies had increased from 0.92 to 2.35 per 100 ED visits (Figure 1, p-value for trend<.0001) over time. The overall VTE rate was 2.35 (95% CI: 2.34-2.37) per 100 ED visits [Table 1, DVT: 1.34 (95% CI: 1.33-1.35) per 100 ED visits; PE: 1.30 (95% CI: 1.29-1.31) per 100 ED visits]. Patients with pancreatic cancer had the highest rate (5.84 per 100 ER visits), followed by lung (3.51 per 100 ER visits) and stomach cancers (3.09 per 100 ER visits) (Figure 2). Patients with thyroid, head and neck and prostate cancers had the lowest rates. Cancer patients with VTE had a higher rate of death in the ED (6.5% vs 4% of those without VTE, p-value<.0001) and a higher rate of admission (92% vs 61% of those without VTE, p-value< .0001). From 2006-2012, the total median hospital cost of cancer patients with VTE increased from $26,069 to $34,254 and were consistently higher than those without VTE (costs: $19,013 to $26,768, Table 2). In the subgroup of patients with solid tumor cancer (N=5,349,246), VTE diagnosis was independently associated with higher odds of admission (adjusted odds ratio (AOR):6.7, 95% CI: 6.56-6.84, p-value< .0001) and hospital death (AOR: 1.24, 95% CI: 1.21-1.27, p-value< .0001) after adjusting for age, cancer types, and metastatic status.ConclusionsVTE diagnosed in the ED was associated with higher rate of mortality, hospital admissions, and healthcare-associated costs. Imaging studies for VTE are increasingly frequent, suggesting increased awareness by ED providers. Future clinical trials are warranted to investigate the cost-effectiveness of outpatient VTE prophylaxis among cancer patients in order to reduce VTE-associated burden. [Display omitted] DisclosuresKhorana:Halozyme: Consultancy, Honoraria; Janssen Scientific Affairs, LLC: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria; Bayer: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Research Funding; Leo: Consultancy, Honoraria, Research Funding.

PERCEPTION OF CANCER PATIENTS ON CHEMOTHERAPY SIDE EFFECTS

Chemotherapy causes various side effects that can affect the patient's physical or non-physical condition. Patients' perceptions or ratings of these side effects vary. This study aimed to identify cancer patients' perceptions of the side effects of chemotherapy they are undergoing. The descriptive study was conducted on 84 samples, namely cancer patients aged 20 years who had undergone chemotherapy at least once before. Data collection using a questionnaire that has been tested for validity and reliability. Data analysis was carried out descriptively with frequency distribution. The results showed that the perception of the physical side effects of chemotherapy that was considered very disturbing by the patient (severe symptoms) was nausea (59.5%), feeling of weakness (36.9%), hair loss (35.7%), vomiting. (29.8%), loss of appetite (28.6%). %), weight loss (27.4%), insomnia and skin discoloration (19% each), headache (16.7%) and fever (15.5%). When the perception of non-physical side effects was fear of death, affecting work/household duties and feeling fear (15.5% each), feeling anxious about my life, and the presence of family members I have to take care (14.3% each). The most disturbing side effects of chemotherapy are physical problems. The health service is expected to increase interventions to minimize the side effects of chemotherapy.

Sensitivity of Psychosocial Distress Screening to Identify Cancer Patients at Risk for Financial Hardship During Care Delivery.

Patients with cancer frequently encounter financial hardship, yet systematic strategies to identify at-risk patients are not established in care delivery. We assessed sensitivity of distress-based screening to identify patients with cancer-related financial hardship and associated care delivery outcomes. A survey of 225 patients at a large cancer center assessed cancer-related financial hardship (0-10 Likert scale; highest quintile scores ≥ 5 defined severe hardship). Responses were linked to electronic medical records identifying patients' distress screening scores 6 months presurvey (0-10 scale) and outcomes of missed cancer care visits and bad debt charges (unrecovered patient charges) within 6 months postsurvey. A positive screen for distress was defined as score ≥ 4. We analyzed screening test characteristics for identifying severe financial hardship within 6 months and associations between financial hardship and outcomes using logistic models. Although patients with positive distress screens were more likely to report financial hardship (odds ratio [OR], 1.21; 1.08-1.37; P < .001), a positive distress screen was only 48% sensitive and 70% specific for identifying severe financial hardship. Patients with worse financial hardship scores were more likely to miss oncology care visits within 6 months (for every additional point in financial hardship score from 0 to 10, OR, 1.28; 1.12-1.47; P < .001). Of patients with severe hardship, 72% missed oncology visits versus 35% without severe hardship (P = .006). Patients with worse hardship were more likely to incur any bad debt charges within 6 months (OR, 1.32; 1.13-1.54; P < .001). Systematic financial hardship screening is needed to help mitigate adverse care delivery outcomes. Existing distress-based screening lacks sensitivity.

Evaluating a high-dimensional machine-learning model to predict hospital mortality among elderly cancer patients.

1512 Background: Elderly hospitalized cancer patients face high risks of inpatient hospital mortality. Identifying patients at high risk of hospital mortality could help with risk stratification, and potentially help inform future interventions aimed at improving outcomes. We evaluated the predictive capacity of a high-dimensional machine-learning prediction tool to predict inpatient mortality, and compared the performance of this new tool to existing prediction indices. Methods: We identified cancer patients 75 and over who presented to an emergency department (ED) and were subsequently hospitalized from the National Emergency Department Sample (NEDS) between 2016 and 2018. We used an extreme gradient boosting approach to predict the risk of death during hospitalization. Model covariates included patient demographics, hospital characteristics, and International Classification of Diseases, version 10 (ICD-10) diagnosis codes recorded during the ED visit. The data were split 75%/25% into training/testing datasets. We constructed the model with training data and evaluated performance within the test data using area under the curve (AUC), with an AUC of 1.0 indicating perfect prediction. We compared the performance of this risk prediction model to standard prediction indices including the Hospital Frailty Risk Score, modified 5-item frailty index, and Charlson comorbidity index. Results: We identified 1,892,690 weighted-hospitalizations among elderly cancer patients, of which 133,379 (7.0%) who died in the inpatient setting. Our final predictive model included 238 features, which contained 5 demographic variables, 3 hospital characteristics, and 230 ICD-10 diagnosis codes. The predictive model achieved an AUC of 0.92. Our comparator models including the Hospital Frailty Risk Score, modified 5-item frailty index, and Charlson comorbidity index achieved AUCs of 0.67, 0.56, and 0.60, respectively. Conclusions: Using a high-dimensional machine-learning model enabled a high level of precision in predicting hospital mortality among elderly cancer patients, substantially out-performing existing prediction indices. High-dimensional prediction models show promise in helping to identify patients at risk of severe adverse outcomes, though additional validation is needed as well as research studying how to implement these tools into practice.