ABSTRACT
OPINION STATEMENT: Treatment strategies for esophageal adenocarcinoma patients continue to advance with the generation of more data from clinical trials that are permitting us to refine the use of immunotherapy in combination with other treatment modalities. While the frontline therapy for metastatic esophageal adenocarcinoma has become more complicated with the approval of combination regimens, it is also yielding better outcomes. These treatment strategies can now be individualized to fit patient circumstances and goals as well as the biomarker profile of their individual tumors leading to an increased likelihood of treatment related remissions and extended median survivals. Comprehensive genomic profiling at diagnosis should now be standard to allow the management team to customize each patient's treatment plan based on the genetic abnormalities discovered in their tumor. By refining these targeted approaches, we will see decreased toxicities and increased survival.
ABSTRACT
Background: We provide care for the rural, low-income, and underserved population of Oroville. The community has a vaccination rate of 50% and booster rate of over 20% in the 3rd year of the ongoing global SARS-CoV-2 pandemic in 2022. During this period, a subset of our cancer patients benefited from the use of immune checkpoint inhibitors. Methods: This is a cross-sectional observational study of the effectiveness of a mRNA-based vaccine in medical care workers compared to patients with systemic malignancies treated with immunomodulation of PD-1 and CTLA-4 inhibitors. The study was approved by the hospital IRB. We evaluated the total anti-Spike protein antibody titer using a commercial semi-quantitative assay, Labcorp Test #164090. All subjects received 3 doses of the mRNA vaccine. We excluded anyone who was administered therapeutic monoclonal antibodies (mAb) or had a recent infection within 120 days. Results: Subjects with systemic malignancies were significantly older, p = 0.0001 by t-test: median age: 76, range: 64-82, compared to health care workers: median age: 52, range: 21-75. Accrual had to be prematurely stopped upon the arrival of Omicron wave in the community. Out of the seven subjects treated with immunomodulation, six received nivolumab, including two in combination with ipilimumab. One subject received pembrolizumab. Six of the subjects had metastatic disease: one was treated adjuvantly for locally advanced esophageal adenocarcinoma. The rest had NSCLC and one case of urothelioma. We divided the groups to those who had the highest titer of antibody versus everybody else and found a similar distribution in both groups using the Chi2 test. The vast majority of the healthcare workers, 24/27 or 89%, had above the upper limit antibody titer. Patients with systemic malignancy, 5/7 or 71%, had above the upper limit antibody titer p = N.S. Conclusions: Three doses of the mRNA vaccine provided high titers irrespective of frailty or age. We hypothesize that immunomodulation could favorably affect vaccination response.
ABSTRACT
Background: Induction FOLFOX followed by PET-directed CRT prior to surgery demonstrated positive results in the CALGB 80803 study. We investigated the safety and efficacy of adding D, an anti-PD-L1 antibody, to PET-directed CRT. Methods: Patients (pts) with locally advanced esophageal/GEJ adenocarcinoma were enrolled. Pts received 2 cycles of mFOLFOX6 prior to repeat PET/CT. PET responders (≥35% reduction in SUV (PETr)) received 5-FU/capecitabine and oxaliplatin with RT to 50.4Gy, while induction PET non-responders (PETnr) received carboplatin/paclitaxel with RT. All Pts received D 1,500 mg q4W ×2 starting 2 weeks prior to CRT. Esophagectomy was planned 6-8 weeks after CRT. Pts with R0 resections received adjuvant D 1,500mg q4W ×6. The primary endpoint was the pathologic complete response (pCR) rate. Results: 36 pts were enrolled. Clinical ≥T3 disease was seen in 32 pts (88.9%, cT4 = 3) and ≥N1 in 23 (63.9%) pts. PD-L1 CPS was ≥1 in 25 (71.4%) of 35 tested with 14 (40%) ≥5. Microsatellite instability (MSI) was identified in 3 (8.3%) pts. 25 (70%) pts were PETr. Preop treatment was well tolerated with no new safety signals. Three pts had disease progression prior to surgery. pCR was identified in 8 (22.2%) pts and 22 (64.7%) had major pathologic response (MPR;ypTanyN0 + ≥90% response). Those with MSI tumors had ≥90% treatment response (1 pCR, 1: ypT1aN0 99% response, 1: ypT2N0, 90% response). 17 (73.9%) of 23 cN+ pts had ypN0 disease. MPR was associated with PD-L1 ≥1 (p = 0.03) and with a higher tumor mutational burden (TMB;p = 0.016) on MSK-IMPACT testing. Adjuvant D was commenced in 27 pts, with a median number of 6 cycles. Early discontinuation was due to risks of visits due to COVID19 (4, 15%), progressive disease (3, 11%), late surgical complications (2, 7%) and immune toxicity (1, 4%). With a median follow-up of 30 months, OS rates were 92% [95%CI: 83%-100%] and 85 % [95%CI: 74%-98%] at 12 and 24 months post induction. 12 and 24-month PFS rates were 81% [95%CI: 69%-95%] and 71% [95%CI: 58%-88%] respectively. In the 33 operated pts, 12 and 24-month disease free survival was 82% [95%CI: 70%-96%] and 78% [95%CI: 65%-94%], respectively. In addition to SUV on PET, total lesion glycolysis (TLG) was correlated with pathologic response. In cases with borderline change in SUV, TLG could predict response to treatment. One PETnr with 30.8% reduction in SUV had 88.1% reduction in TLG and pCR. Conversely, a PETr (-36.3%) who had an increase in TLG (39.3%) had only 40% treatment response on pathology. Conclusions: The addition of D to induction FOLFOX and PETdirected CRT prior to surgery is safe and appears effective with a high rate of pathologic response, as well as encouraging survival data. PD-L1 CPS≥1 and higher TMB may be associated with MPR. TLG is a novel PET variable that should be studied prospectively. Additional correlatives and comparison to a cohort treated with standard PET-directed CRT will be presented.
ABSTRACT
Introduction Previously our group had identified 20 features which were associated with the development of upper gastrointestinal (UGI) cancers using a machine learning approach.[1] We sought to refine this model and to validate this in an independent dataset to assess its generalisability in an interim analysis. Methods We selected patients who were recruited for the multicentre Saliva to Predict rIsk of disease using Transcriptomics and epigenetics (SPIT) study to develop our model. Patients were recruited from 2-week wait suspected UGI pathways and additionally enriched with patients with confirmed oesophageal adenocarcinoma admitted as inpatients. We used regularised logistic regression (glmnet) from the caret package in R software to create the model. 60% of the data with 10-fold cross validation was used for training, with the remaining 40% for testing. For validation, we used data from the predicting RIsk of disease uSing detailed Questionnaires (RISQ) study, an ongoing prospective multicentre study using the questionnaire based on the our previous work.1 We evaluated the model using area under the receiver operating characteristic curve (AUC). Results We included 93 cancer and 715 non-cancer patients for training and testing and 21 cancer and 203 non-cancer patients for validation. We further reduced the model to 18 features without significant detriment to model performance. In the training and testing data AUC was 0.86 (95%CI: 0.81- 0.91) and 0.75 (95%CI: 0.67-0.83) respectively. We set a threshold of 0.03 as a cut off based on a cost function where false negatives had a 50-time greater impact than false positive cases (figure 1). For the validation cohort we achieved an AUC of 0.95 (95%CI: 0.90-1.00). This equated to a sensitivity 0.952 and a specificity of 0.897 for detecting cancer. Conclusions Initial results from our model compare favourably with the Edinburgh Dysphagia Scale, which has a sensitivity and specificity of 0.984 and 0.093 respectively.2 It also appears to have a high specificity, potentially helping to reduce unnecessary endoscopies. We aim to further increase the size of the validation cohort to ensure its robustness and generalisability. Our model could be applied to triaging and prioritising endoscopic referral backlogs as a result of COVID- 19.3.
ABSTRACT
Introduction Machine learning methods have been used to develop predictive models in gastroenterology.1 Previously we identified features including age, history of psychological disorders and severity of dysphagia symptoms which were correlated with upper gastrointestinal (UGI) cancers.2 We sought to create a machine learning based model which could be used to predict the presence of UGI in patients referred for endoscopy. Methods Patients were recruited as part of the Saliva to Predict rIsk of disease using Transcriptomics and epigenetics (SPIT) study. Patients were recruited from 2-week wait suspected UGI pathway referrals at 20 hospitals in the United Kingdom. We enriched the cohort with additional patients admitted with confirmed oesophageal adenocarcinoma. 60% of the data was used for model generation with 10-fold cross validation, while the models were tested on the remaining 40% of the data. We used seven methods to generate our models: Linear Discriminant Analysis (lda), Classification and Regression Tree (cart), k-Nearest Neighbour (knn), Support Vector Machines (svm), Random Forest (rf), Logistic Regression (glm) and Regularised Logistic Regression (glmnet). Model performance was assessed using area under the receiver operating characteristic curve (AUC) and DeLong test was used for model comparison. Results 93 cancer and 715 non-cancer patients were included. The best three models with 18 features were glmnet, lda and glm which all achieved an AUC of greater than 0.80 (figure 1). For the testing dataset, AUC was 0.75 (95%CI: 0.67- 0.83), 0.74 (95%CI: 0.66-0.82) and 0.75 (95%CI: 0.68-0.83) (p=ns for all 3 pairwise comparisons) respectively. When applying a cost function, the three models all achieved a sensitivity of 0.973 and a specificity of 0.234 to 0.388 for the testing dataset. Conclusions Our models compare favourably with the Edinburgh Dysphagia Scale, which has a sensitivity and specificity of 0.984 and 0.093 respectively.3 Our models have the advantage of an improved specificity, which could equate to fewer endoscopies being performed for low risk patients. Given rising waiting lists as a direct result of COVID-19, our tool could be used to prioritise patients who should be investigated sooner.4 We plan next to validate our models on a validation cohort to assess its generalisability.
ABSTRACT
Background and aim: Covid-19 has had a devastating global impact and resulted in over 4.4 million directly attributed deaths. The UK entered lockdown in March 2020, redistributing its medical workforce and resources. Early estimations suggested at least 4700 extra cancer deaths at 5 years if there was a 3-month delay to surgery. Delays to diagnosis and treatment for esophagogastric (EG) cancers can be particularly detrimental to survival. The aim of this study is to assess the impact of Covid-19 on new cancer referrals to a centralised UK EG cancer centre, including presentation, decision making and treatment. Methods: Patients with EG cancer referred to a tertiary, high-volume centre between March 2019 and March 2021 were reviewed. Patients were stratified into Pre-covid (March 2019-March 2020) and Covid (March 2020- 2021) cohorts. Number of new referrals, clinical stage, treatment decision, and time to treatment were compared for gastric adenocarcinoma (GA), esophagogastric-junction adenocarcinoma (EGJA), esophageal adenocarcinoma (EA) and esophageal SCC (ESCC). Results: There was an 11% reduction in new cancer referrals (485 vs 431). GA, EGJA and EA did not have significant change in treatment intent, although there was a significant increase in the decision for definitive nonsurgical treatment of EA (P = 0.046). GA and EA patients had a small, but significant increase in average clinical stage at presentation (P < 0.05). There was no increase in time to treatment for GA, EGJA and EA. A significantly higher proportion of ESCC patients were given curative intent treatment in the Covid-19 cohort (P = 0.0006) however, this was accompanied with an increased time to treatment (35.8 days vs 27.9 days P = 0.0198). Conclusion: This high-volume centre has seen a reduction in new cancer referrals since the first UK lockdown. This was associated with a small, but significant, increase in clinical stage of GA and EA at presentation. This may represent an early indication of excess esophagogastric cancer deaths due to the impact of Covid-19. This data also confirms initial results showing that oncological decisions were not compromised, although Covid-19 remains a dynamic challenge.
ABSTRACT
DDW 2022 Author Disclosures: Sachin Wani: NO financial relationship with a commercial interest ;Jeffrey Williams: NO financial relationship with a commercial interest ;Jennifer Holub: NO financial relationship with a commercial interest ;Audrey Calderwood: YES financial relationship with a commercial interest;Dark Canyon Laboratoties:Advisory Committees or Review Panels ;Jason Dominitz: NO financial relationship with a commercial interest ;Prasad Iyer: YES financial relationship with a commercial interest;Exact Sciences:Consulting;Exact Sciences:Grant/Research Support;Pentax:Grant/Research Support;Pentax:Consulting;Ambu:Consulting;Symple Surgical:Consulting;Medtronic:Consulting ;Nicholas Shaheen: YES financial relationship with a commercial interest;Lucid:Grant/Research Support;Medtronic:Grant/Research Support;Steris:Grant/Research Support;Pentax:Grant/Research Support;CDx Medical:Consulting;Cernostics:Consulting;Interpace Diagnostics:Grant/Research Support;Phathom Pharmaceuticals:Consulting;Exact Sciences:Consulting;Aqua Medical:Consulting;Cook Medical:Consulting Background: The COVID-19 pandemic has disrupted endoscopy practices with significant reductions in procedural capacity creating unprecedented decreases in cancer screening and surveillance services. Using a national registry with matched endoscopy and pathology data, we aimed to assess the impact of the pandemic on the proportion of patients diagnosed with BE and BE-related dysplasia and adherence to established quality indicators in BE. Methods: We analyzed data from the GI Quality Improvement Consortium (GIQuIC) Registry, a national repository of endoscopy data. Procedure data from all EGDs in the registry during the study period, including procedure indication, demographics, endoscopy findings, pathology results and recommendations were assessed from 1/2018 – 5/2021. Three cohorts based on date of EGD performance were created: Pre-pandemic (1/2018-2/2020), Early Pandemic (3/2020-7/2020) and Late-pandemic (8/2020-5/2021). Observed and expected number of BE and dysplasia cases/month were calculated. Adherence to Seattle protocol was assessed by dividing the BE length by number of pathology jars submitted;a ratio of ≤2.0 with rounding down was considered adherent. Adherence to recommended surveillance for non-dysplastic BE (NDBE) was calculated by assessing the proportion recommended to undergo an EGD between 3-5 years. Results: Among 1,619,684 EGDs assessed, 94,081 (5.8%) met inclusion criteria (Table 1). These cases were largely performed by GIs and represented 394 practices and 2666 endoscopists nationwide with geographic distribution within the U.S. as follows: West 24%, Midwest 13%, South 40%, and Northeast 23%. Fewer endoscopies were performed by non-GIs during the early (1.5%) and late pandemic (1.5%) compared to pre-pandemic period (9.3%, p<0.001). The mean BE length was 2.3 (2.5) cm and distribution based on histology was NDBE 87.5%, low-grade dysplasia (LGD) 2.2%, indefinite for dysplasia (IND) 2.9%, high-grade dysplasia (HGD) 1.5%, and unknown 5.8%. Table and Figure highlight the significant reduction in the number of patients diagnosed with BE (47.9% and 24.1%) and BE-related dysplasia (HGD: 38.5% and 25.3%;LGD: 45% and 34%, any dysplasia: 43.9% and 31.3%) per month during the early and late pandemic periods. Over the pandemic, there was no decline in adherence rates to quality indicators in BE with an overall adherence rate to the Seattle protocol and appropriate recommended surveillance interval in NDBE of 83% and 68.4%, respectively. Conclusions: Results of this study demonstrate a significant decline in EGD volume with an associated reduction in the number of patients diagnosed with BE and related dysplasia during the COVID-19 pandemic. The absence of a compensatory increase in diagnoses in the late pandemic period is concerning with likely long-term deleterious downstream effects on esophageal adenocarcinoma morbidity and mortality. [Formula presented] [Formula presented]
ABSTRACT
A 42-year-old female with a past medical history of femoral facial syndrome (FFS) and years of gastroesophageal reflux disease presented to our clinic with symptoms of dysphagia and iron deficiency anemia. On upper endoscopy, esophageal stricture and adenocarcinoma were detected. Unfortunately, the patient developed coronavirus disease 2019 (COVID-19) multi-organ failure prior to cancer treatment and died with dignity after choosing comfort care measures. To the best of our knowledge, we report the first case of FFS in an adult patient. This case also uniquely highlights the rare gastrointestinal manifestations of FFS.
ABSTRACT
Introduction Waiting times for endoscopy are rising rapidly following the COVID-19 pandemic. In addition, cancers may be missed as patients are placed on routine waiting lists but not monitored. Some hospitals use the Edinburgh Dysphagia Score to assess and prioritise patients for investigation. This offers a sensitivity of 98.4% and specificity of 9.3% to detect malignancy in patients presenting with dysphagia.4 However, it is not designed for detecting gastric cancer. We aimed to create a more accurate screening questionnaire as an aid to triaging referrals. Methods Patients were recruited as part of the Saliva to Predict rIsk of disease using Transcriptomics and epigenetics (SPIT) study. Patients were recruited from 2 week-wait suspected upper gastrointestinal cancer pathway referrals at 20 hospitals in the United Kingdom. The cohort was further enriched with patients found to have oesophageal adenocarcinoma on emergency hospital admission. They completed over 200 questions about a wide variety of symptoms and risk factors. After data cleaning, 800 patients were available for evaluation. Of these, 80 had upper GI cancer. A machine learning model was developed to identify those at highest risk of having upper GI cancer using a 'cost-based' approach which maximises the chance of detecting cancer. Information gain was followed by correlated feature selection and a multivariable logistic regression curve was created with scores from 0 (cancer very unlikely) to 100 (cancer very likely). The training dataset used 80% of the data and the model was tested with the other 20%. Results 20 features were found to be important and reproducible. They included age, sex, dysphagia, odynophagia, early satiety, weight loss, duration of chest pain and regurgitation, frequency of acid taste in the mouth, a previous history of smoking, cancer or psychological disorders, current anxiety level and frequency of vegetable intake. The area under the receiver operator curve to detect cancer was 0.83. 50% of cancers scored greater than 85 whereas 50% of normals scored less than 25. At a cut-off score of 10, sensitivity was 98.7% with specificity 26.8% to detect cancer (figure). Conclusions We have created a simple, reproducible risk score to identify patients at high and low risk of upper GI cancer. It performs better than previous scores but now needs testing in the real world. It might be usable to both upgrade routine patients to urgent endoscopy and remove patients at very low risk from waiting lists, thereby helping to prioritise patients with a greater clinical need and reducing the endoscopic backlog.