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Background: The phase 1b/2 CARTITUDE-1 study (NCT03548207) is evaluating ciltacabtagene autoleucel (cilta-cel; JNJ-68284528; LCAR-B38M CAR-T cells), a chimeric antigen receptor T (CAR-T) cell therapy with 2 B-cell maturation antigen-targeting single-domain antibodies, in patients with relapsed/refractory (R/R) multiple myeloma (MM). Cytokine release syndrome (CRS), a known side effect of CAR-T therapy, can be mild to life-threatening and requires careful monitoring and management. Here, we analyzed CRS and cytokine profiles in CARTITUDE-1. Methods: Eligible patients (aged ≥18 years) had a diagnosis of MM per International Myeloma Working Group criteria, measurable disease, Eastern Cooperative Oncology Group performance status ≤1, received ≥3 prior regimens or were double-refractory to a proteasome inhibitor and immunomodulatory drug, and received an anti-CD38 antibody. Bridging therapy was permitted after apheresis. At 5-7 days prior to cilta-cel infusion, lymphodepletion was performed with cyclophosphamide 300 mg/m2 and fludarabine 30 mg/m2 daily for 3 days. Cilta-cel was administered as a single infusion at a target dose of 0.75×106 (range: 0.5-1.0×106) CAR+ viable T cells/kg. CRS was graded using Lee et al (Blood 2014) in the phase 1b portion and American Society for Transplantation and Cellular Therapy (ASTCT) in the phase 2 portion. In this combined analysis, Lee et al criteria were mapped to ASTCT criteria for patients in the phase 1b portion. Serum samples for cytokine profiling were collected prior to lymphodepletion, prior to cilta-cel infusion and 2 hours post-infusion on Day 1, at regular time points until Day 100, and if CRS was suspected or reported. Results: A total of 97 patients with R/R MM were treated with cilta-cel; median follow-up for this analysis was 8.8 months (range: 1.5-20.4). CRS was reported in 92 (94.8%) patients. A total of 48 (49.5%) patients had grade 1 CRS, 38 (39.2%) had grade 2, 4 (4.1%) had grade 3, and 1 had grade 5 (1.0%); maximum toxicity grade according to the ASTCT consensus grading system could not be derived for 1 patient with CRS in the phase 1b portion. Median time to CRS onset from cilta-cel infusion was 7.0 days (range: 1-12). Median duration of CRS was 4.0 days (range: 1-27, excluding n=1 with 97 days). Supportive measures to treat CRS or CRS symptoms were administered to 87 (89.7%) patients, most commonly tocilizumab (69.1%), acetaminophen (68.0%), corticosteroids (20.6%), and anakinra (18.6%). CRS resolved in 91 (98.9%) patients; the patient with grade 5 CRS/hemophagocytic lymphohistiocytosis died on Day 99 subsequent to sequelae of grade 4 CRS. Across all patients, levels of interleukin (IL)-6, IL-10, and interferon-γ peaked at Days 7-14 post-cilta-cel infusion. Conclusions: CRS after cilta-cel treatment was low grade and manageable in most patients with R/R MM. The low rate of grade ≥3 CRS, median time to CRS onset of 7.0 days, and median duration of 4.0 days suggests outpatient dosing of cilta-cel may be feasible; this approach is being explored in the phase 2 CARTITUDE-2 study (NCT04133636). Disclosures Lin: Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite, a Gilead Company: Consultancy, Research Funding; Vineti: Consultancy; Takeda: Research Funding; Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding. Martin:Janssen: Research Funding; AMGEN: Research Funding; Sanofi: Research Funding; Seattle Genetics: Research Funding; GSK: Consultancy. Cohen:Novartis: Other: Patents/Intellectual property licensed, Research Funding; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda,: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Genentech/Roche: Membership on an entity's Board of Directors or advisory committees. Jakubowiak:AbbVie, Amgen, BMS/Celgene, GSK, Janssen, Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive, Juno: Consultancy, Honoraria. Usmani:Celgene: Other; Takeda: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; SkylineDX: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Pharmacyclics: Research Funding; GSK: Consultancy, Research Funding; Janssen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Array Biopharma: Research Funding; Merck: Consultancy, Research Funding; Abbvie: Consultancy; BMS, Celgene: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Amgen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Incyte: Research Funding. Madduri:AbbVie: Consultancy, Honoraria; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Foundation Medicine: Consultancy, Honoraria; Legend: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Kinevant: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau. Stewart:Janssen, BMS, Sanofi-Aventis, GSK: Honoraria; Tempus, Inc., Genomics England LLC: Membership on an entity's Board of Directors or advisory committees. Singh:Janssen: Current Employment. Zudaire:Janssen: Current Employment. Yeh:Janssen: Current Employment. Allred:Janssen: Current Employment. Olyslager:Janssen: Current Employment. Banerjee:Janssen: Current Employment. Goldberg:Johnson & Johnson: Current Employment, Current equity holder in publicly-traded company. Schecter:Janssen: Current Employment. Jackson:Memorial Sloan Kettering Cancer Center: Consultancy; Janssen: Current Employment. Deraedt:Janssen: Current Employment, Current equity holder in publicly-traded company. Geng:Legend Biotech USA Inc.: Current Employment. Wu:Legend Biotech USA Inc.: Current Employment. Carrasco:Legend Biotech USA Inc.: Current Employment. Akram:Legend Biotech USA Inc.: Current Employment. Hossain:Legend Biotech USA Inc.: Current Employment. Wang:Legend Biotech USA Inc.: Current Employment. Berdeja:CRISPR Therapeutics: Consultancy, Research Funding; EMD Sorono: Research Funding; Teva: Research Funding; Servier: Consultancy; Vivolux: Research Funding; Abbvie: Research Funding; Novartis: Research Funding; Janssen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Karyopharm: Consultancy; Kesios: Research Funding; Kite Pharma: Consultancy; Legend: Consultancy; Genentech, Inc.: Research Funding; BMS: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Cellularity: Research Funding; Constellation: Research Funding; Glenmark: Research Funding; CURIS: Research Funding; Bioclinica: Consultancy; Amgen: Consultancy, Research Funding; Bluebird: Research Funding; Poseida: Research Funding; Acetylon: Research Funding; Prothena: Consultancy; Lilly: Research Funding. Jagannath:BMS, Janssen, Karyopharm, Legend Biotech, Sanofi, Takeda: Consultancy.

Background Patients with myeloproliferative neoplasms (MPNs) are faced with severe disease-related fatigue among a range of other constitutional and spleen-related symptoms. The MPN-Symptom Assessment Form (SAF) is recommended for use to characterize symptom burden (Scherber R, et al. Blood 2011). Within the SAF, a profile of 18 symptom items are evaluated ranging in severity from 0 (absent) to 10 (worst imaginable). The SAF is often summarized to the MPN-SAF Total Symptom Score (TSS) for analysis purposes - a single computed sum of the 10 most clinically meaningful symptom scores, including fatigue (Emanuel R, et al. J Clin Oncol 2012). Though the SAF includes a fatigue item, initial deployments of the MPN-SAF TSS incorporated a 0-10 scaled fatigue item taken from the Brief Fatigue Inventory (BFI; Mendoza T, et al. Cancer 1999). A subsequent version of the MPN-SAF TSS for use within myelofibrosis clinical trials (called the MFSAF v4; Gwaltney C, et al. Leuk Res 2017) employed a harmonized fatigue item. This analysis employing data from two studies was carried out to assess the use of the SAF fatigue item within the MPN-SAF TSS for consistency with the MFSAF v4. Methods Both BFI and SAF fatigue items were included in an initial online survey evaluating disease burden among patients with MPNs. Participants were assigned to survey variants as a function of their age. Survey variants included those to receive 1 instance of either the BFI or SAF fatigue item, instances of both BFI and SAF, or 2 instances of the same fatigue item. Surveying was aimed to assess the worst symptom experience in the patient's last 24 hours. Additionally, an independent survey assessing the impact of COVID-19 among MPN patients was deployed using the SAF fatigue item for the MPN-SAF TSS. This modified version was then used to test internal validity. Pearson correlation (r) and t-tests were used to assess association, Bland-Altman methods were used to evaluate systematic agreement between BFI and SAF fatigue scores, and Cronbach's alpha was used to measure internal consistency. Results There were 229 participants assigned both BFI and SAF fatigue items within the same survey. Among them, 51% (n=117) received the BFI item first and 49% (n=112) the SAF item first. No difference was seen between first and second fatigue scores (mean difference [first-second] = 0.00; 95%CI -0.18, 0.17). BFI and SAF fatigue scores were highly correlated (r=0.88, p<0.001) and showed 88.7% agreement in categorizing severe versus non-severe fatigue (score ≥ 7 versus < 7). Overall concordance in severity category was 73.4% (category [score range]: absent [0]; mild [1-3]; moderate [4-6]; severe [7-10]). Constructing the MPN-SAF TSS using the BFI and SAF fatigue components separately, the original and modified MPN-SAF TSS were nearly identical (r=0.997, p<0.001), and had equivalent internal consistency (both Cronbach's alpha=0.88). The Bland-Altman plot further indicates the 2 fatigue measures have high agreement with no evidence of directional bias and negligible overall bias (Figure 1: regression slope = -0.04, p=0.25; mean difference=0.22; 95%CI 0.05, 0.39). Within the COVID-19 survey (n=1217), the modified version of the MPN-SAF TSS was consistent with known correlates among disease characteristics (Emanuel R, et al. J Clin Oncol 2012). For example, more severe MPN-SAF TSS scores were highly correlated with low quality-of-life (n=1156, r = -0.50, p<0.001), and associated with those reporting spleen enlargement (n=301) versus not (n=617) (p<0.001; mean difference=7.7; 95%CI 5.4, 10.1). Conclusion The BFI and SAF fatigue items are highly consistent in raw score, severity category, and in contribution to the MPN-SAF TSS. There was no order effect seen in which fatigue item was asked first. The independent COVID-19 survey using the modified MPN-SAF TSS was validated and shows high internal consistent. In the ongoing development to capture the symptom experience, this analysis shows disease-related fatigue is equivalently measured using the SAF fatigue survey item in harmonization with the MFSAF v4. Disclosures Mesa: Bristol Myers Squibb: Research Funding; CTI BioPharma: Research Funding; Promedior: Research Funding; AbbVie: Research Funding; Samus Therapeutics: Research Funding; Genentech: Research Funding; Incyte: Research Funding; LaJolla Pharmaceutical Company: Consultancy; Novartis: Consultancy; Sierra Oncology: Consultancy.

Abstract Background. —Under the auspices of the College of American Pathologists, the current state of knowledge regarding pathologic prognostic factors (factors linked to outcome) and predictive factors (factors predicting response to therapy) in colorectal carcinoma was evaluated. A multidisciplinary group of clinical (including the disciplines of medical oncology, surgical oncology, and radiation oncology), pathologic, and statistical experts in colorectal cancer reviewed all relevant medical literature and stratified the reported prognostic factors into categories that reflected the strength of the published evidence demonstrating their prognostic value. Accordingly, the following categories of prognostic factors were defined. Category I includes factors definitively proven to be of prognostic import based on evidence from multiple statistically robust published trials and generally used in patient management. Category IIA includes factors extensively studied biologically and/or clinically and repeatedly shown to have prognostic value for outcome and/or predictive value for therapy that is of sufficient import to be included in the pathology report but that remains to be validated in statistically robust studies. Category IIB includes factors shown to be promising in multiple studies but lacking sufficient data for inclusion in category I or IIA. Category III includes factors not yet sufficiently studied to determine their prognostic value. Category IV includes factors well studied and shown to have no prognostic significance. Materials and Methods. —The medical literature was critically reviewed, and the analysis revealed specific points of variability in approach that prevented direct comparisons among published studies and compromised the quality of the collective data. Categories of variability recognized included the following: (1) methods of analysis, (2) interpretation of findings, (3) reporting of data, and (4) statistical evaluation. Additional points of variability within these categories were defined from the collective experience of the group. Reasons for the assignment of an individual prognostic factor to category I, II, III, or IV (categories defined by the level of scientific validation) were outlined with reference to the specific types of variability associated with the supportive data. For each factor and category of variability related to that factor, detailed recommendations for improvement were made. The recommendations were based on the following aims: (1) to increase the uniformity and completeness of pathologic evaluation of tumor specimens, (2) to enhance the quality of the data needed for definitive evaluation of the prognostic value of individual prognostic factors, and (3) ultimately, to improve patient care. Results and Conclusions. —Factors that were determined to merit inclusion in category I were as follows: the local extent of tumor assessed pathologically (the pT category of the TNM staging system of the American Joint Committee on Cancer and the Union Internationale Contre le Cancer [AJCC/UICC]); regional lymph node metastasis (the pN category of the TNM staging system); blood or lymphatic vessel invasion; residual tumor following surgery with curative intent (the R classification of the AJCC/UICC staging system), especially as it relates to positive surgical margins; and preoperative elevation of carcinoembryonic antigen elevation (a factor established by laboratory medicine methods rather than anatomic pathology). Factors in category IIA included the following: tumor grade, radial margin status (for resection specimens with nonperitonealized surfaces), and residual tumor in the resection specimen following neoadjuvant therapy (the ypTNM category of the TNM staging system of the AJCC/UICC). Factors in category IIB included the following: histologic type, histologic features associated with microsatellite instability (MSI) (ie, host lymphoid response to tumor and medullary or mucinous histologic type), high degree of MSI (MSI-H), loss of heterozygosity at 18q ( DCC gene allelic loss), and tumor border configuration (infiltrating vs pushing border). Factors grouped in category III included the following: DNA content, all other molecular markers except loss of heterozygosity 18q/DCC and MSI-H, perineural invasion, microvessel density, tumor cell–associated proteins or carbohydrates, peritumoral fibrosis, peritumoral inflammatory response, focal neuroendocrine differentiation, nuclear organizing regions, and proliferation indices. Category IV factors included tumor size and gross tumor configuration. This report records findings and recommendations of the consensus conference group, organized according to structural guidelines defined herein.

Objective Interactive patient care systems (IPCS) at the bedside are becoming increasingly common, but evidence is limited as to their potential for innovative clinical trial implementation. The objective of this study was to test the hypothesis that the IPCS could feasibly be used to automate recruitment and enrolment for a clinical trial. Methods In medical-surgical units, we used the IPCS to randomise, recruit and consent eligible subjects. For participants not interacting with IPCS study materials within 48 hours, study staff-initiated recruitment in-person. Eligible study population included all caregivers and any patients >6 years old admitted to medical-surgical units and oncology units September 2015 to January 2016. Outcomes: randomisation assessed using between-group comparisons of patient characteristics; recruitment success assessed by rates of consent; paperless implementation using successful acquisition of electronic signature and email address. We used χ2 analysis to assess success of randomisation and recruitment. Results Randomisation was successful (n=1012 randomised, p>0.05 for all between-group comparisons). For the subset of eligible, randomised patients who were recruited, IPCS-only recruitment (consented: 2.4% of n=213) was less successful than in-person recruitment (61.4% of n=87 eligible recruited, p<0.001). For those consenting (n=61), 96.7% provided an electronic signature and 68.9% provided email addresses. Conclusions Our results suggest that as a tool at the bedside, the IPCS offers key efficiencies for study implementation, including randomisation and collecting e-consent and contact information, but does not offer recruitment efficiencies. Further research could assess the value that interactive technologies bring to recruitment when paired with in-person efforts, potentially focusing on more intensive user-interface testing for recruitment materials. Trial registration number NCT02491190.

Background: Microfracture (MF) has been used historically to treat osteochondral lesions of the talus (OLTs), with favorable outcomes reported in approximately 80% to 85% of cases. However, MF repairs have been shown to degrade over time at long-term follow-up, suggesting that further study into optimal OLT treatment is warranted. The use of adjuvant extracellular matrix with bone marrow aspirate concentrate (ECM-BMAC) has not been extensively evaluated in the literature. We present a comparison of patient-reported and radiographic outcomes following ECM-BMAC repair vs traditional MF. Methods: Patients who underwent MF (n = 67) or ECM-BMAC (n = 62) treatment for an OLT were identified and their charts were retrospectively reviewed. Postoperative magnetic resonance imaging (MRI) was evaluated and patient-reported outcome scores, either Foot and Ankle Outcome Scores (FAOS) or Patient-Reported Measurement Information System (PROMIS) scores, were collected. MRIs were scored by a radiologist, fellowship trained in musculoskeletal radiology, using the Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) system. Radiographic and clinical outcomes were compared between groups. Results: On average, patients treated with ECM-BMAC demonstrated a higher total MOCART score compared to the MF group (73 ± SD 11.5 vs 54.0 ± 24.1; P = .0015). ECM-BMAC patients also had significantly better scores for the Infill, Integration, and Signal MOCART subcategories. Last, patients treated with ECM-BMAC had a lower rate of revision compared to those treated with MF (4.8% vs 20.9%; P = .007). FAOS scores were compared between groups, with no significant differences observed. Conclusion: When comparing outcomes between patients treated for an OLT with ECM-BMAC vs traditional MF, we observed superior MRI results for ECM-BMAC patients. The rate of revision surgery was higher for MF patients, although patient-reported outcomes were similar between groups. The use of ECM-BMAC as an adjuvant therapy in the treatment of OLTs may result in improved reparative tissue when compared to MF. Level of Evidence: Level III, comparative series.

Analysis of CD4 + T cell heterogeneity in the lung uncovers a Bcl6-dependent subset that supports mucosal antibody production.

Abstract Hashimoto encephalopathy, also known as steroid-responsive encephalopathy associated with autoimmune thyroiditis, has been defined by sub-acute onset encephalopathy, with elevated thyroid antibodies, and immunotherapy responsiveness, in the absence of specific neural autoantibodies. We aimed to retrospectively review 144 cases referred with suspected Hashimoto encephalopathy over a 13-year period, and to determine the clinical utility of thyroid antibodies in the course of evaluation of those patients. One hundred and forty-four patients (all thyroid antibody positive) were included; 72% were women. Median age of symptom onset was 44.5 years (range, 10–87). After evaluation of Mayo Clinic, 39 patients (27%) were diagnosed with an autoimmune CNS disorder [autoimmune encephalopathy (36), dementia (2) or epilepsy (1)]. Three of those 39 patients had neural-IgGs detected (high glutamic acid decarboxylase-65, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor-receptor and neural-restricted unclassified antibody), and 36 were seronegative. Diagnoses among the remaining 105 patients (73%) were functional neurological disorder (n = 20), neurodegenerative disorder (n = 18), subjective cognitive complaints (n = 14), chronic pain syndrome (n = 12), primary psychiatric (n = 11), sleep disorder (n = 10), genetic/developmental (n = 8), non-autoimmune seizure disorders (n = 2) and other (n = 10). More patients with autoimmune CNS disorders presented with sub-acute symptom onset (P &lt; 0.001), seizures (P = 0.008), stroke-like episodes (P = 0.007), aphasia (P = 0.04) and ataxia (P = 0.02), and had a prior autoimmune history (P = 0.04). Abnormal brain MRI (P = 0.003), abnormal EEG (P = 0.007) and CSF inflammatory findings (P = 0.002) were also more frequent in the autoimmune CNS patients. Patients with an alternative diagnosis had more depressive symptoms (P = 0.008), anxiety (P = 0.003) and chronic pain (P = 0.002). Thyoperoxidase antibody titre was not different between the groups (median, 312.7 versus 259.4 IU/ml; P = 0.44; normal range, &lt;9 IU/ml). None of the non-autoimmune group and all but three of the CNS autoimmune group (two with insidious dementia presentation, one with seizures only) fulfilled the autoimmune encephalopathy criteria proposed by Graus et al. (A clinical approach to diagnosis of autoimmune encephalitis. Lancet Neurol 2016; 15: 391–404.) (sensitivity, 92%; specificity, 100%). Among patients who received an immunotherapy trial at our institution and had objective post-treatment evaluations, the 16 responders with autoimmune CNS disorders more frequently had inflammatory CSF, compared to 12 non-responders, all eventually given an alternative diagnosis (P = 0.02). In total, 73% of the patients referred with suspected Hashimoto encephalopathy had an alternative non-immune-mediated diagnosis, and more than half had no evidence of a primary neurological disorder. Thyroid antibody prevalence is high in the general population, and does not support a diagnosis of autoimmune encephalopathy in the absence of objective neurological and CNS-specific immunological abnormalities. Thyroid antibody testing is of little value in the contemporary evaluation and diagnosis of autoimmune encephalopathies.

The NCCN Guidelines for Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic focus primarily on assessment of pathogenic or likely pathogenic variants associated with increased risk of breast, ovarian, and pancreatic cancer and recommended approaches to genetic testing/counseling and management strategies in individuals with these pathogenic or likely pathogenic variants. This manuscript focuses on cancer risk and risk management for BRCA-related breast/ovarian cancer syndrome and Li-Fraumeni syndrome. Carriers of a BRCA1/2 pathogenic or likely pathogenic variant have an excessive risk for both breast and ovarian cancer that warrants consideration of more intensive screening and preventive strategies. There is also evidence that risks of prostate cancer and pancreatic cancer are elevated in these carriers. Li-Fraumeni syndrome is a highly penetrant cancer syndrome associated with a high lifetime risk for cancer, including soft tissue sarcomas, osteosarcomas, premenopausal breast cancer, colon cancer, gastric cancer, adrenocortical carcinoma, and brain tumors.

AbstractBackgroundPrimary mesenteric soft tissue sarcomas (STS) are rare and limited evidence is available to inform management. Surgical resection is challenging due to the proximity of vital structures and a need to preserve enteric function.ObjectivesTo determine the overall survival (OS) and recurrence‐free survival (RFS) for patients undergoing primary resection for mesenteric STS.MethodsThe Trans‐Atlantic Australasian Retroperitoneal Sarcoma Working Group (TARPSWG) is an intercontinental collaborative comprising specialist sarcoma centers. Data were collected retrospectively for all patients with mesenteric STS undergoing primary resection between 2000 and 2019.ResultsFifty‐six cases from 15 institutions were included. The spectrum of pathology was similar to the retroperitoneum, although of a higher grade. R0/R1 resection was achieved in 87%. Median OS was 56 months. OS was significantly shorter in higher‐grade tumors (p = .018) and extensive resection (p < .001). No significant association between OS and resection margin or tumor size was detected. Rates of local recurrence (LR) and distant metastases (DM) at 5 years were 60% and 41%, respectively. Liver metastases were common (60%), reflecting portal drainage of the mesentery.ConclusionPrimary mesenteric sarcoma is rare, with a modest survival rate. LR and DM are frequent events. Liver metastases are common, highlighting the need for surveillance imaging.