Cardio-oncology in advanced prostate cancer.

Treatment intensification with androgen deprivation therapy (ADT) and androgen receptor pathway inhibitors (ARPi) have led to improved survival in advanced prostate cancer. However, ADT is linked to significant cardiovascular toxicity, and ARPi also negatively impacts cardiovascular health. Together with a higher prevalence of baseline cardiovascular risk factors reported among prostate cancer survivors at diagnosis, there is a pressing need to prioritise and optimise cardiovascular health in this population. Firstly, While no dedicated cardiovascular toxicity risk calculators are available, other tools such as SCORE2 can be used for baseline cardiovascular risk assessment. Next, selected patients on combination therapy may benefit from de-escalation of ADT to minimise its toxicities while maintaining cancer control. These patients can be characterised by an exceptional PSA response to hormonal treatment, favourable disease characteristics and competing comorbidities that warrant a less aggressive treatment regime. In addition, emerging molecular and genomic biomarkers hold the potential to identify patients who are suited for a de-escalated treatment approach either with ADT or with ARPi. One such biomarker is AR-V7 splice variant that predicts resistance to ARPi. Lastly, optimization of modifiable cardiovascular risk factors for patients through a coherent framework (ABCDE) and exercise therapy is equally important. This article aims to comprehensively review the cardiovascular impact of hormonal manipulation in metastatic hormone-sensitive prostate cancer, propose overarching strategies to mitigate cardiovascular toxicity associated with hormonal treatment, and, most importantly, raise awareness about the detrimental cardiovascular effects inherent in our current management strategies involving hormonal agents.

Real-world outcomes of pemetrexed-platinum chemotherapy plus osimertinib after progression on first-line osimertinib in advanced EGFR-mutated NSCLC.

OBJECTIVES: First-line pemetrexed-platinum chemotherapy + osimertinib(Pem-Plat-Osi) improves progression-free survival as compared to osimertinib alone in advanced epidermal growth factor (EGFR)-mutated non-small cell lung cancer (NSCLC). However, many patients are hesitant to commence chemotherapy upfront. We describe outcomes to Pem-Plat-Osi after first-line osimertinib failure. MATERIALS AND METHODS: Patients with advanced EGFR-mutated (ex19del/L858R) NSCLC who had Pem-Plat-Osi between 1/7/2018-30/9/2023 after progression on first-line osimertinib at National Cancer Centre Singapore, Prince of Wales Hospital and Chinese University of Hong Kong were identified. Key endpoints were time to treatment failure (TTF) and overall survival (OS). RESULTS: A total of 60 patients were included. Median age at diagnosis was 62, 53.3 % (32/60) were male and 76.7 % (46/60) were never smokers. Ex19del comprised 56.7 % (34/60) and L858R 43.3 % (26/60). Baseline central nervous system (CNS) metastases were present in 66.7 % (40/60). Median TTF on osimertinib (TTF1) was 14.4 months(m) and median time to initiation of Pem-Plat-Osi was 41 days(d) (range 0-652) after progression on osimertinib. Partial response (PR) or stable disease to Pem-Plat-Osi was achieved in 81.7 %(49/60). Intracranial disease control was achieved in 90.6 % (29/32) of patients with measurable CNS metastases, including those who did not undergo brain radiotherapy. At median follow up of 31.2 m, median TTF on Pem-Plat-Osi (TTF2) was 6.6 m. Median TTF1 + TTF2 was 23.4 m and median OS was 34.2 m. Survival outcomes were similar comparing ex19del and L858R (median TTF1 + TTF2 21.8 m vs 23.5 m, p = 0.90; median OS 34.2 m vs 36.8 m, p = 0.37) and in patients without/with baseline CNS metastases (median TTF1 + TTF2 21.8 m vs 23.4 m, p = 0.44; median OS 36.2 m vs 31.9 m, p = 0.65). TTF1 duration was not significantly associated with TTF2 (p = 0.76). Patients who started Pem-Plat-Osi within 20d of progression on osimertinib had significantly longer TTF2 as compared to patients who started after 20d (median 8.4 m versus 6.0 months, p = 0.03), which remained statistically significant on multivariable analysis. CONCLUSIONS: Our real-world data supports the efficacy of Pem-Plat-Osi after progression on first-line osimertinib, including L858R and baseline CNS metastases. Chemotherapy initiation within 20d of Osi progression was predictive of superior TTF2.

Brief Report: Droplet Digital Polymerase Chain Reaction Versus Plasma Next-Generation Sequencing in Detecting Clearance of Plasma EGFR Mutations and Carcinoembryonic Antigen Levels as a Surrogate Measure.

Introduction: To compare the performance of droplet digital polymerase chain reaction (ddPCR) and plasma next-generation sequencing (NGS) in detecting clearance of plasma EGFR (pEGFR) mutations. Methods: Patients with treatment-naive advanced EGFR-mutated lung cancer treated with first-line tyrosine kinase inhibitors (TKIs) were included. pEGFR were measured at baseline and first response assessment using ddPCR and NGS. Clearance of pEGFR was defined as undetectable levels after a positive baseline result. Results were correlated with time-to-treatment failure (TTF). In exploratory analysis, corresponding change in carcinoembryonic antigen (CEA) levels was evaluated. Results: Between January 1, 2020, and December 31, 2021, 27 patients were recruited. Ex19del comprised 74% (20 of 27) and L858R 26% (seven of 27). Osimertinib was used in 59% (16 of 27), dacomitinib 4% (one of 27), and gefitinib/erlotinib 37% (10 of 27). Sensitivity of ddPCR and NGS in detecting pEGFR mutation at baseline was 70% (19 of 27) and 78% (21 of 27), respectively (p = 0.16). All patients with detectable pEGFR by ddPCR were detected by NGS.At a median of 8 (range 3-24) weeks post-TKI initiation, clearance of pEGFR was achieved in 68% (13 of 19) and 71% (15 of 21) using ddPCR and NGS, respectively. Concordance between ddPCR and NGS was 79% (kappa = 0.513, p = 0.013). Clearance of pEGFR was associated with longer median TTF (not reached versus 6 months, p = 0.03) and median decrease in CEA levels by 70% from baseline.In another cohort of 124 patients, decrease in CEA levels by greater than 70% within 90 days of TKI initiation was associated with doubling of both TTF and overall survival. Conclusions: Plasma NGS trended toward higher sensitivity than ddPCR in detecting pEGFR, although both had similar concordance in detecting pEGFR clearance. Our results support using NGS at diagnosis and interchangeability of NGS and ddPCR for monitoring, whereas CEA could be explored as a surrogate for pEGFR clearance.

COVID-19 Severity and Waning Immunity After up to 4 mRNA Vaccine Doses in 73 608 Patients With Cancer and 621 475 Matched Controls in Singapore: A Nationwide Cohort Study.

Importance: Despite patients with cancer being at risk of poor outcomes from COVID-19, there are few published studies for vaccine efficacy in this group, with suboptimal immunogenicity and waning vaccine efficacy described in small studies being a concern. Objective: To assess the incidence rate of severe COVID-19 disease outcomes associated with the number of vaccine doses received and the waning of protection over time. Design, Setting, and Participants: A prospective multicenter observational cohort study was carried out over 2 time periods (September 15, 2021, to December 20, 2021 [delta wave], and January 20, 2022, to November 11, 2022 [omicron wave]) predominated by SARS-CoV-2 delta and omicron variants, respectively. Overall, 73 608 patients with cancer (23 217 active treatment, 50 391 cancer survivors) and 621 475 controls matched by age, sex, race and ethnicity, and socioeconomic status were included. Exposure: Vaccine doses received, from zero to 4 doses, and time elapsed since last vaccine dose. Outcomes: Competing-risk regression analyses were employed to account for competing risks of death in patients with cancer. Main outcomes were incidence rate ratios (IRRs) of COVID-19 infection, hospitalization, and severe disease (defined as requirement for supplemental oxygen, intensive care, or death). The IRRs stratified by time from last vaccine dose served as indicators of waning of vaccine effectiveness over time. Results: The mean (SD) age of actively treated patients with cancer, cancer survivors, and controls were 62.7 (14.7), 62.9 (12.6), and 61.8 (14.7) years, respectively. Of 73 608 patients with cancer, 27 170 (36.9%) were men; 60 100 (81.6%) were Chinese, 7432 (10.1%) Malay, 4597 (6.2%) Indian, and 1479 (2.0%) were of other races and ethnicities. The IRRs for the 3-dose and 4-dose vs the 2-dose group (reference) for COVID-19 hospitalization and severe disease were significantly lower during both the delta and omicron waves in cancer and control populations. The IRRs for severe disease in the 3-dose group for active treatment, cancer survivors, and controls were 0.14, 0.13, and 0.07 during the delta wave and 0.29, 0.19, and 0.21 during omicron wave, respectively. The IRRs for severe disease in the 4-dose group during the omicron wave were even lower at 0.13, 0.10 and 0.10, respectively. No waning of vaccine effectiveness against hospitalization and severe disease was seen beyond 5 months after a third dose, nor up to 5 months (the end of this study's follow-up) after a fourth dose. Conclusion: This cohort study provides evidence of the clinical effectiveness of mRNA-based vaccines against COVID-19 in patients with cancer. Longevity of immunity in preventing severe COVID-19 outcomes in actively treated patients with cancer, cancer survivors, and matched controls was observed at least 5 months after the third or fourth dose.

Inferring cancer disease response from radiology reports using large language models with data augmentation and prompting.

OBJECTIVE: To assess large language models on their ability to accurately infer cancer disease response from free-text radiology reports. MATERIALS AND METHODS: We assembled 10 602 computed tomography reports from cancer patients seen at a single institution. All reports were classified into: no evidence of disease, partial response, stable disease, or progressive disease. We applied transformer models, a bidirectional long short-term memory model, a convolutional neural network model, and conventional machine learning methods to this task. Data augmentation using sentence permutation with consistency loss as well as prompt-based fine-tuning were used on the best-performing models. Models were validated on a hold-out test set and an external validation set based on Response Evaluation Criteria in Solid Tumors (RECIST) classifications. RESULTS: The best-performing model was the GatorTron transformer which achieved an accuracy of 0.8916 on the test set and 0.8919 on the RECIST validation set. Data augmentation further improved the accuracy to 0.8976. Prompt-based fine-tuning did not further improve accuracy but was able to reduce the number of training reports to 500 while still achieving good performance. DISCUSSION: These models could be used by researchers to derive progression-free survival in large datasets. It may also serve as a decision support tool by providing clinicians an automated second opinion of disease response. CONCLUSIONS: Large clinical language models demonstrate potential to infer cancer disease response from radiology reports at scale. Data augmentation techniques are useful to further improve performance. Prompt-based fine-tuning can significantly reduce the size of the training dataset.

Breast metastasis from endometrial clear cell carcinoma: A case report and review of the literature.

Metastasis to the breast from extra-mammary malignancies are rare, accounting for less than 1% of all breast cancers. Endometrial cancer, a common gynecological malignancy, often spreads to the pelvis, abdominal lymph nodes, peritoneum or the lungs. Endometrial metastasis to the breast is extremely rare, and while there have been isolated case reports of endometrial serous carcinoma with breast metastasis, it has not been reported in the case of clear cell carcinoma. We present a rare case of a 70 year old Chinese lady who had a metastatic endometrial clear cell carcinoma with metastasis to the breast, mimicking an inflammatory breast cancer clinically. We reviewed the current literature and describe the challenges in differentiating primary from metastatic breast lesions, as well as clinical, radiological and histopathological features that may help to differentiate the two. Tumour metastasis to the breast via lymphatic or hematogenous route can affect their radiological features: the former mimicking inflammatory breast cancer and the latter with features similar to benign breast lesions. Regardless, histological features with immunohistochemical staining is still the gold standard in diagnosing metastatic breast lesions and determining their tissue of origin. Breast metastases from extra-mammary malignancies are uncommon and it is even rarer for endometrial clear cell carcinoma to spread to the breast. Nonetheless, this case highlights the importance of keeping an open mind and engaging a multidisciplinary team for the care of complex patients.

Hydration effects on the efficacy of the Epidermal growth factor receptor kinase inhibitor afatinib.

Small molecules targeting the EGFR tyrosine kinase domain have been used with some success at treating patients with non-small cell lung cancer driven by activating mutations in the kinase domain. The initial class of inhibitors displaced ATP noncovalently but were rendered ineffective due to the development of resistance mutations in the kinase domain. These were overcome by the development of covalent inhibitors such as afatinib which also bind in the ATP pocket. However pooled analysis of two recent clinical trials LUX-3 and LUX-6 demonstrated an unprecedented overall survival benefit of afatinib over chemotherapy for the EGFR 19del , but not the EGFR L858R . In the current study we use modelling and simulations to show that structural constraints in EGFR 19del deletion result in significantly attenuated flexibilities in the binding pocket resulting in strong hydrogen and halogen bonds with afatinib in the EGFR 19del ; these constraints are modulated by buried water and result in the differential affinities of afatinib for the different mutants. SNP analysis of residues surrounding the buried water points to the likelihood of further differential effects of afatinib and provides a compelling case for investigating the effects of the SNPs towards further stratification of patients for ensuring the most effective use of afatinib.