Immunogenicity of the BNT162b2 mRNA COVID-19 vaccine in patients with primary brain tumors: a prospective cohort study.

PURPOSE: Immunogenicity of Covid-19 vaccines may be negatively impacted by anti-cancer treatment. The management of primary brain tumors (PBTs) routinely includes temozolomide and steroids, which are immune-suppressive. We aimed to determine the rate of seropositivity in PBT patients following receipt of two doses of the BNT162b2 vaccine. METHODS: We prospectively evaluated IgG levels against SARS-CoV-2 spike protein in 17 PBT patients following two doses of the BNT162b2 vaccine. IgG levels were collected at two time points: T1-after a median of 44 days from the second vaccine dose and T2-after a median of 130 days from the second dose. Titers were compared against a group of healthy controls (HC) comprised of patients' family members. RESULTS: At T1, 88.2% (15/17) of PBT patients achieved seroconversion, compared with 100% (12/12) of HCs. Median IgG titer was significantly lower in the PBT group (1908 AU/mL vs 8,198 AU/mL; p = 0.002). At T2, 80% (12/15) of PBT patients seroconverted, compared to 100% (10/10) of HCs. Median IgG titer remained significantly lower in the PBT group (410 AU/mLvs 1687 AU/mL; p = 0.002). During the peri-vaccination period, 15 patients received systemic treatment and 8 patients were treated with corticosteroids. All 3 patients who failed to seroconvert at T2 were treated with corticosteroids. In a univariate analysis, steroid use was negatively associated with antibody titer. CONCLUSION: Most PBT patients successfully seroconvert following two doses of the BNT162b2 vaccine, albeit with lower antibody titer compared to HCs. Steroid use during the vaccination period is associated with lower titer.

Improving Cardiovascular Disease Prediction Using Automated Coronary Artery Calcium Scoring from Existing Chest CTs.

Cardiovascular disease (CVD) prediction models are widely used in modern medicine and are incorporated into prominent guidelines. Coronary artery calcium (CAC) is a marker of coronary atherosclerotic disease and has proven utility for predicting cardiovascular disease. Despite this, current guidelines recommend against including CAC scores in CVD prediction models due to the medical and financial costs of acquiring it, and the insufficient evidence concerning its ability to improve existing models. Modern machine learning models are capable of automatically extracting coronary calcium scores from existing chest computed tomography (CT) scans, negating these costs. To determine whether the inclusion of CAC scores, automatically extracted using a machine learning algorithm from chest CTs performed for any reason, improves the performance of the American Heart Association/American College of Cardiology 2013 pooled cohort equations (PCE). A retrospective cohort of patients with available chest CTs prior to an index date (2012) was used to compare the performance of the PCE model and an augmented-PCE model which utilizes the CT-based CAC scores on top of the existing model. The PCE and the augmented-PCE predictions were calculated as of an index date (2012) using data from the electronic health record and existing chest CTs. The performance of both models was evaluated by comparing their predictions to cardiovascular events that occurred during a 5-year follow-up period (until 2017). A total of 14,135 patients aged 40-79 years were included in the study, of whom 470 (3.3%) had documented CVD events during the follow-up. The augmented-PCE model showed a significant improvement in c-statistic (0.64 ≥ 0.69, Δ = 0.05, 95% CI: 0.03 to 0.06), sensitivity (53% ≥ 57%, Δ = 4.7%, 95% CI: 0-9.0%), specificity (67% ≥ 70%, Δ = 2.8%, 95% CI: 0.9-5.1%), in positive predictive value (5% ≥ 6%, Δ = 0.9%, 95% CI: 0.4 to 1.4%), negative predictive value (97.7% ≥ 97.9%, Δ = 0.3%, 95% CI: 0.1 to 0.5%), and in the categorical net reclassification index (7.4%, 95% CI: 2.4 to 12.1%). Automatically generated CAC scores from existing CTs can aid in CVD risk determination, improving model performance when used on top of existing predictors. Use of existing CTs avoids most pitfalls currently cited against the routine use of CAC in CVD predictions (e.g., additional radiation exposure), and thus affords a net gain in predictive accuracy.

Immunotherapy in mismatch repair-deficient metastatic colorectal cancer - Outcome and novel predictive markers.

BACKGROUND: This study aims to assess predictive markers for response to immunotherapy in dMMR/MSI-H metastatic colorectal cancer (mCRC) patients. MATERIALS AND METHODS: A study using two prospective cohorts from MD Anderson Cancer Center and Sheba Medical Center of consecutive patients with dMMR/MSI-H mCRC that were treated with immunotherapy between 2014-2022. Primary outcome was progression-free survival (PFS) and secondary outcome was overall response rate (ORR). Evaluated predictors included ECOG-PS score, RAS/BRAF status, single-agent versus doublet immunotherapy, metastatic sites, disease burden, and CEA levels prior to treatment initiation. Kaplan-Meier analysis and Cox proportional hazard regression model were used to analyze the effect of exposure variables on PFS. RESULTS: The study included 153 patients. Median follow-up time was 26 months (IQR 11-48). Median PFS was 51.6 months (95%CI 38.1-NR) and ORR was 58.1%. In a univariate analysis, male sex was associated with worse PFS with a HR of 1.67 (95% CI 1.00-2.79); Right-sided tumors were associated with improved PFS with a HR of 0.56 (95% CI 0.32-0.97); Liver or lung metastasis were associated with worse PFS with HRs of 2.35 (95%CI 1.43-3.88) and 2.30 (95%CI 1.31-4.04), respectively; ECOG-PS score ≥ 2, CEA levels ˃5 µg/L prior to treatment initiation and ≥ 3 metastatic sites were associated with worse PFS with HRs of 2.09 (95%CI 0.98-4.47), 2.23 (95%CI 1.30-3.81) and 3.11 (95%CI 1.61-6.03), respectively. Liver or lung metastasis remained significant in a multivariable model. CONCLUSIONS: Extent of disease (worse PFS with high CEA, poor ECOG-PS and ≥3 metastatic sites) and disease location (worse PFS with liver or lung metastasis and left sided tumor) were associated with immunotherapy outcome in dMMR/MSI-H mCRC.

Real-world evidence for immunotherapy in the first line setting in small cell lung cancer.

OBJECTIVE: Despite major progress over the past decade in the field of lung cancer care, only mild advances have occurred in Small Cell Lung Cancer (SCLC), with prognosis remaining poor. Based on two randomized clinical trials (RCTs), two checkpoint-inhibitors have recently been approved in extensive-SCLC with moderate improvements in median overall survival (OS). However, only limited data exist regarding the impact of immunotherapy in real-world SCLC patients. This study reports the efficacy of immunotherapy in the first-line treatment of extensive-stage SCLC patients in a real-world setting. METHODS: a retrospective cohort study of all patients treated for extensive-SCLC with chemotherapy with or without immunotherapy, at a single center in Israel between October-2017 and July-2021. Patient characteristics, adverse-events and survival analyses were conducted. RESULTS: Of 102 patients identified, 54 patients (53%) received immunotherapy in addition to chemotherapy. 34.7% of patients had a performance status (PS) of 2-4. Patients that received only chemotherapy were older, had more liver metastasis and a poorer PS. In the whole cohort, patients receiving immunotherapy had a significantly longer median OS (353 days vs 194 days, HR = 0.40p < 0.0001). After stratification by PS groups, survival analysis remained significantly longer in the PS 0-1 group (HR 0.43, p = 0.0036), with a trend for better survival in the PS 2-3 group. Multivariate analysis validated an OS advantage with immunotherapy (HR = 0.46, p = 0.004). CONCLUSION: We present evidence for the efficacy of immunotherapy in SCLC in a real-world setting. Although treatment groups differ in their baseline characteristics, it appears that even some patients not included in RCTs, such as poor PS, may benefit from the addition of immunotherapy to their treatment protocol.

Humoral and T-Cell Response before and after a Fourth BNT162b2 Vaccine Dose in Adults ≥60 Years.

Both humoral and cellular anamnestic responses are significant for protective immunity against SARS-CoV-2. In the current study, the responses in elderly people before and after a fourth vaccine dose of BNT162b2 were compared to those of individuals immunized with three vaccine doses. Although a boost effect was observed, the high response following the third administration questions the necessity of an early fourth boost.

Palbociclib in combination with sunitinib exerts a synergistic anti-cancer effect in patient-derived xenograft models of various human cancers types.

The efficacy/safety of combining palbociclib (a CDK4/6 inhibitor) and sunitinib (a multi-targeted receptor tyrosine kinase inhibitor) was evaluated, using patient-derived xenograft (PDX) models. Twenty-three PDX mice models were developed from patients with various solid tumors. The mice were randomized to 4 groups (5-6 mice in each): control/palbociclib (100 mg/kg)/sunitinib (50 mg/kg)/combination. Drugs were administered orally, 5 days/week. In 17/23 PDX models (74%), the combination demonstrated a synergistic inhibitory effect vs the monotherapies ("responder" models) with no unexpected toxicities. In 13/17 responder models, where standard-of-care (SOC) was an additional comparator, the combination was more effective than SOC in 7 models, as effective in 4, and less effective in 2. The mean ± SEM experiment duration in 15/17 responder models (2/17 were excluded due to technical issues) was 86 ± 12 and 31 ± 5 days for the combination and control groups, respectively (p = 0.0002). The effect of the combination was dose-dependent. Cell-viability experiments in A549/MDA-MB-231/HT-29 cell lines and experiments using tumor-derived primary cell spheroids supported the PDX findings. In conclusion, combination of palbociclib and sunitinib exerts a synergistic anti-tumor effect without adding unexpected toxicity. A clinical trial assessing this combination is underway.

Three-month follow-up of durability of response to the third dose of the SARS-CoV-2 BNT162b2 vaccine in adults aged 60 years and older: a prospective cohort study.

OBJECTIVE: To evaluate the durability of response 3 months after the third BNT162b2 vaccine in adults aged 60 years and older. DESIGN: Prospective cohort study. SETTING: Single tertiary centre. PARTICIPANTS: Healthcare workers/family members aged ≥60 years old who received the third BNT162b2 dose. INTERVENTIONS: Blood samples were drawn immediately before (T0), 10-19 days (T1) and 74-103 days (T2) after the third dose. PRIMARY AND SECONDARY OUTCOME MEASURES: Anti-spike IgG titres were determined using a commercial assay and seropositivity was defined as ≥50 arbitrary units (AU)/mL. Neutralising antibody titres were determined at T2. Adverse events, COVID-19 infections and Clinical Frailty Scale (CFS) levels were documented. RESULTS: The analysis included 97 participants (median age, 70 years (IQR, 66-74), 58% CFS level 2). IgG titres, which increased significantly from T0 to T1 (median, 440 AU/mL (IQR, 294-923) and median, 25 429 AU/mL (IQR, 14 203-36 114), respectively; p<0.001), decreased significantly by T2, but all remained seropositive (median, 8306 AU/mL (IQR, 4595-14 701), p<0.001 vs T1). In a multivariable analysis, only time from the second vaccine was significantly associated with lower IgG levels at T2 (p=0.017). At T2, 60 patients were evaluated for neutralising antibodies; all were seropositive (median, 1294 antibody titres; IQR, 848-2072). Neutralising antibody and anti-spike IgG levels were correlated (r=0.6, p<0.001). No major adverse events or COVID-19 infections were reported. CONCLUSIONS: Anti-spike IgG and neutralising antibody levels remain adequate 3 months after the third BNT162b2 vaccine in healthy adults aged ≥60 years, although the decline in IgG is concerning. A third dose of vaccine in this population should be top priority.

Selective Intra-Arterial Doxorubicin Eluting Microsphere Embolization for Desmoid Fibromatosis: A Combined Prospective and Retrospective Study.

Desmoid fibromatoses (DFs) are locally aggressive tumors composed of monoclonal fibroblasts within an abundant extracellular matrix. Systemic doxorubicin treatment is effective, but toxic. We investigated arterial doxorubicin eluting embolization (DEE), an approach characterized by high drug concentrations in the tumor alongside limited systemic drug exposure. The primary and secondary endpoints were radiological response using MRI and RECIST 1.1, respectively. The study included 24 patients (median age, 24; interquartile range, 16-34 years). Data were collected prospectively for 9 patients and retrospectively for 15 patients. The most frequent tumor locations were chest/abdomen wall and neck/shoulder/axilla (29% each). Of 24 patients, 7 (24%) were treatment naïve, and 17 (71%) had received one or two prior treatments. Patients underwent a median of two treatments (range, 1-4), with a median of 49 mg (range, 8-75) doxorubicin/treatment. Efficacy outcomes were available for 23 patients. With a median follow-up of 8 months (interquartile range, 3-13), median tumor volumes decreased by 59% (interquartile range, 40-71%) and T2 signal intensity decreased by 36% (interquartile range, 19-55%). Of 23 patients, 9 (39%), 12 (52%), and 2 (9%) had a partial response, stable disease, and progressive disease, respectively. DEE was safe and well tolerated, with one reported grade 3-4 adverse event (cord injury). In conclusion, DEE was safe and achieved rapid clinical/volumetric responses in DFs.

Real-World Analysis of the Impact of Radiotherapy on Immunotherapy Efficacy in Non-Small Cell Lung Cancer.

BACKGROUND: Immunotherapy (IO) provides a significant benefit for a subgroup of non-small cell lung cancer (NSCLC) patients. Radiotherapy (XRT) might enhance the efficacy of IO. We evaluated the impact of the specifics of XRT treatments on the OS of IO-treated NSCLC patients. METHODS: Metastatic NSCLC patients treated with IO were retrospectively identified. Parameters included demographics, tumor characteristics, IO and XRT details. Correlation between the parameters and OS was tested with Cox regression. RESULTS: 453 patients were included. No XRT was given to 167 (36.9%) patients, whereas XRT prior and after IO had 182 (40.2%) and 104 (22.9%) patients, respectively. XRT total doses between 30 and 40 Gy had better overall survival (OS) compared to non-irradiated patients (hazard ratio (HR) 0.5, 95% CI 0.25-1.0, p = 0.049). Worse outcome was seen with total doses ≤ 10 Gy (HR 1.67, 95% 1.13-2.5, p = 0.01), XRT fractions of 4.1-8 Gy (HR 1.48, 95% CI 1.05-2.1, p = 0.027) and XRT to the bone (HR 1.36, 95% CI 1.01-1.8, p = 0.04). Several clinical parameters correlated with OS in the univariate analysis of the IO-treated patients. While, in the multivariate analysis, only ECOG-PS, treatment line, type of IO, albumin and NLR remained statistically significant. CONCLUSION: Specific doses, fractions and sites of XRT correlated with the OS of IO-treated NSCLC patients in the univariate analysis, although not in the multivariate analysis.

Evaluation of Seropositivity Following BNT162b2 Messenger RNA Vaccination for SARS-CoV-2 in Patients Undergoing Treatment for Cancer.

Importance: Patients with cancer undergoing treatment are at high risk of COVID-19 following SARS-CoV-2 infection; however, their ability to produce an adequate antibody response to messenger RNA SARS-CoV-2 vaccines is unclear. Objective: To evaluate rates of antispike (anti-S) antibody response to a BNT162b2 vaccine in patients with cancer who are undergoing systemic treatment vs healthy controls. Design, Setting, and Participants: This prospective cohort study included 102 adult patients with solid tumors undergoing active intravenous anticancer treatment and 78 controls who received the second dose of the BNT162b2 vaccine at least 12 days before enrollment. The controls were taken from a convenience sample of the patients' family/caregivers who accompanied them to treatment. The study was conducted between February 22, 2021, and March 15, 2021 at Davidoff Cancer Center at Beilinson Hospital (Petah Tikva, Israel). Interventions: Blood samples were drawn from the study participants. Serum samples were analyzed and the titers of the IgG antibodies against SARS-CoV-2 spike receptor-binding domain were determined using a commercially available immunoassay. Seropositivity was defined as 50 or greater AU/mL. Main Outcomes and Measures: The primary outcome was the rate of seropositivity. Secondary outcomes included comparisons of IgG titers and identifying factors that were associated with seropositivity using univariate/multivariable analyses. Results: The analysis included 180 participants, which comprised 102 patients with cancer (median [interquartile range (IQR)] age, 66 [56-72] years; 58 men [57%]) and 78 healthy controls (median [IQR] age, 62 [49-70] years; 25 men [32%]). The most common tumor type was gastrointestinal (29 [28%]). In the patient group, 92 (90%) were seropositive for SARS-CoV 2 antispike IgG antibodies after the second vaccine dose, whereas in the control group, all were seropositive. The median IgG titer in the patients with cancer was significantly lower than that in the controls (1931 [IQR, 509-4386] AU/mL vs 7160 [IQR, 3129-11 241] AU/mL; P < .001). In a multivariable analysis, the only variable that was significantly associated with lower IgG titers was treatment with chemotherapy plus immunotherapy (ß, -3.5; 95% CI, -5.6 to -1.5). Conclusions and Relevance: In this cohort study of patients with cancer who were receiving active systemic therapy, 90% of patients exhibited adequate antibody response to the BNT162b2 vaccine, although their antibody titers were significantly lower than those of healthy controls. Further research into the clinical relevance of lower titers and their durability is required. Nonetheless, the data support vaccinating patients with cancer as a high priority, even during therapy.

Comparison of Poly (ADP-ribose) Polymerase Inhibitors (PARPis) as Maintenance Therapy for Platinum-Sensitive Ovarian Cancer: Systematic Review and Network Meta-Analysis.

BACKGROUND: Three PARPis (olaparib, niraparib and rucaparib) are currently FDA-approved as maintenance therapy in newly diagnosed and recurrent ovarian cancer. However, thus far, no trial has compared the three approved PARPis in the overall population, in patients with BRCA mutations, or in those with wild-type BRCA. METHODS: A frequentist network meta-analysis was used for indirect comparisons between the different PARPis with respect to progression free survival (PFS), overall survival (OS), and adverse events. RESULTS: Overall, six randomized clinical trials involving 2,770 patients, were included in the analysis. Results from the indirect comparisons revealed no statistically significant differences between the three PARPis with respect to PFS or OS in the entire population and in patients with mutated and wild-type BRCA, separately. Niraparib showed a statistically significant increased risk for grade 3 and 4 thrombocytopenia (risk-difference [RD] from placebo: 0.3; 95% confidence interval [CI], 0.27‒0.34) and any grade neutropenia (RD from placebo: 0.22; 95% CI, 0.18‒0.25) as compared with the other PARPis. CONCLUSION: No statistically significant difference was found between the three PARPis with respect to PFS or OS (overall and in subpopulations by BRCA status). There is, however, a statistical difference in toxicity as niraparib is associated with a greater risk for thrombocytopenia and neutropenia.

Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST).

BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that annual screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. Nonetheless, the leading cause of mortality in the study was from cardiovascular diseases. PURPOSE: To determine whether the used machine learning automatic algorithms assessing coronary calcium score (CCS), level of liver steatosis and emphysema percentage in the lungs are good predictors of cardiovascular disease (CVD) mortality and incidence when applied on low dose CT scans. MATERIALS AND METHODS: Three fully automated machine learning algorithms were used to assess CCS, level of liver steatosis and emphysema percentage in the lung. The algorithms were used on low-dose computed tomography scans acquired from 12,332 participants in NLST. RESULTS: In a multivariate analysis, association between the three algorithm scores and CVD mortality have shown an OR of 1.72 (p = 0.003), 2.62 (p < 0.0001) for CCS scores of 101-400 and above 400 respectively, and an OR of 1.12 (p = 0.044) for level of liver steatosis. Similar results were shown for the incidence of CVD, OR of 1.96 (p < 0.0001), 4.94 (p < 0.0001) for CCS scores of 101-400 and above 400 respectively. Also, emphysema percentage demonstrated an OR of 0.89 (p < 0.0001). Similar results are shown for univariate analyses of the algorithms. CONCLUSION: The three automated machine learning algorithms could help physicians to assess the incidence and risk of CVD mortality in this specific population. Application of these algorithms to existing LDCT scans can provide valuable health care information and assist in future research.

Current and Potential Approaches for Defining Disease Signatures: a Systematic Review.

Identifying disease signatures in order to facilitate accurate diagnosis/treatment has been the focus of research efforts in the last decade. However, the term "disease signature" has not been properly defined, resulting in inconsistencies between studies, as well as limited ability to fully utilize the tools/information available in the evolving field of healthcare big data. Research was conducted according to the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. The search (in PubMed, Cochrane, and Web of Science) was limited to English articles published up to 31/12/2016. The search string was "disease signature" OR "disease signatures" OR "disease fingerprint" OR "disease fingerprints" OR "subtype signature" OR "subtype signatures" OR "subgroup signature" OR "subgroup signatures." The full text of the articles was reviewed to determine the meaning of the phrase "disease signature" as well as the context of its use. Of 285 articles identified in the search, 129 were included in the final analysis. The term disease signature was first found in an article from 2001. In the last 10 years, the use of the term increased by approximately ninefold, which is double the general increase in the number of published articles. Only one article attempted to define the term. The two major medical fields where the term was used were oncology (31%) and neurology (20%); 71% of the identified articles used a single biomarker to define the term, 13% of the articles used a pair of biomarkers, and 16% used signatures with multiple biomarker; in 42% of the identified articles, genomic biomarkers were used for the signature, in 17% measurements of biochemical compounds in body fluids, and in 10%, changes in imaging studies were used for the signature. Our findings identified a lack of consistency in defining the term disease signature. We suggest a novel hierarchical multidimensional concept for this term that would combine both current approaches for identifying diseases (one focusing on undesired effects of the disease and the other on its causes). This model can improve disease signature definition consistency which will enable to generalize and classify diseases, resulting in more precise treatments and better outcomes. Ultimately, this model could lead to developing a statistical confidence in a disease signature that would allow physicians/patients to estimate the precision of the diagnosis, which, in turn, may have important implications on patients' prognosis and treatment.