Citations

Abstract Purpose: Clinical trials reported 25% to 30% pathologic complete response (pCR) rates in HER2+ patients with breast cancer treated with anti-HER2 therapies without chemotherapy. We hypothesize that a multiparameter classifier can identify patients with HER2-“addicted” tumors who may benefit from a chemotherapy-sparing strategy. Experimental Design: Baseline HER2+ breast cancer specimens from the TBCRC023 and PAMELA trials, which included neoadjuvant treatment with lapatinib and trastuzumab, were used. In the case of estrogen receptor–positive (ER+) tumors, endocrine therapy was also administered. HER2 protein and gene amplification (ratio), HER2-enriched (HER2-E), and PIK3CA mutation status were assessed by dual gene protein assay (GPA), research-based PAM50, and targeted DNA-sequencing. GPA cutoffs and classifier of response were constructed in TBCRC023 using a decision tree algorithm, then validated in PAMELA. Results: In TBCRC023, 72 breast cancer specimens had GPA, PAM50, and sequencing data, of which 15 had pCR. Recursive partitioning identified cutoffs of HER2 ratio ≥ 4.6 and %3+ IHC staining ≥ 97.5%. With PAM50 and sequencing data, the model added HER2-E and PIK3CA wild-type (WT). For clinical implementation, the classifier was locked as HER2 ratio ≥ 4.5, %3+ IHC staining ≥ 90%, and PIK3CA-WT and HER2-E, yielding 55% and 94% positive (PPV) and negative (NPV) predictive values, respectively. Independent validation using 44 PAMELA cases with all three biomarkers yielded 47% PPV and 82% NPV. Importantly, our classifier's high NPV signifies its strength in accurately identifying patients who may not be good candidates for treatment deescalation. Conclusions: Our multiparameter classifier differentially identifies patients who may benefit from HER2-targeted therapy alone from those who need chemotherapy and predicts pCR to anti-HER2 therapy alone comparable with chemotherapy plus dual anti-HER2 therapy in unselected patients.

Abstract In this multi-institutional retrospective study, we examined the characteristics and outcomes of 160 patients with high-grade B-cell lymphoma, not otherwise specified (HGBL-NOS)—a rare category defined by high-grade morphologic features and lack of MYC rearrangements with BCL2 and/or BCL6 rearrangements ("double hit"). Our results show that HGBL-NOS tumors are heterogeneous: 83% of patients had a germinal center B-cell immunophenotype, 37% a dual-expressor immunophenotype (MYC and BCL2 expression), 28% MYC rearrangement, 13% BCL2 rearrangement, and 11% BCL6 rearrangement. Most patients presented with stage IV disease, a high serum lactate dehydrogenase, and other high-risk clinical factors. Most frequent first-line regimens included dose-adjusted cyclophosphamide, doxorubicin, vincristine, and etoposide, with rituximab and prednisone (DA-EPOCH-R; 43%); rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP; 33%); or other intensive chemotherapy programs. We found no significant differences in the rates of complete response (CR), progression-free survival (PFS), or overall survival (OS) between these chemotherapy regimens. CR was attained by 69% of patients. PFS at 2 years was 55.2% and OS was 68.1%. In a multivariable model, the main prognostic factors for PFS and OS were poor performance status, lactate dehydrogenase >3 × upper limit of normal, and a dual-expressor immunophenotype. Age >60 years or presence of MYC rearrangement were not prognostic, but patients with TP53 alterations had a dismal PFS. Presence of MYC rearrangement was not predictive of better PFS in patients treated with DA-EPOCH-R vs R-CHOP. Improvements in the diagnostic criteria and therapeutic approaches beyond dose-intense chemotherapy are needed to overcome the unfavorable prognosis of patients with HGBL-NOS.

Background: There is a significant long-term risk of posttraumatic osteoarthritis (PTOA) after anterior cruciate ligament reconstruction (ACLR). Elucidating the risk factors and successfully identifying at-risk patients is challenging. Purpose/Hypothesis: The purpose of this study was to produce machine learning survival models that can identify (1) patients at risk of symptomatic PTOA and (2) patients who are at risk of undergoing total knee arthroplasty (TKA) after ACLR. It was hypothesized that these models would outperform traditional Kaplan-Meier estimators. Study Design: Case-control study; Level of evidence, 3. Methods: A geographic database was used to identify patients undergoing ACLR between 1990 and 2016 with a minimum 7.5-year follow-up. Models were used to analyze various factors to predict the rate and time to (1) symptomatic osteoarthritis and (2) TKA using random survival forest (RSF) algorithms. Performance was measured using out-of-bag (OOB) c-statistic, calibration, and Brier score. The predictive performances of the RSF models were compared with Kaplan-Meier estimators. Model interpretability was enhanced utilizing global variable importance and partial dependence curves. Results: A total of 974 patients with ACLR and a minimum follow-up of 7.5 years were included; among these, 215 (22.1%) developed symptomatic osteoarthritis, and 25 (2.6%) progressed to TKA. The RSF algorithms achieved acceptable good to excellent predictive performance for symptomatic arthritis (OOB c-statistic, 0.75; Brier score, 0.128) and progression to TKA (OOB c-statistic, 0.89; Brier score, 0.026), respectively. Significant predictors of symptomatic PTOA included increased pain scores, older age, increased body mass index, increased time to ACLR, total number of arthroscopic surgeries before the diagnosis of arthritis, positive pivot-shift test after reconstruction, concomitant chondral injury, secondary meniscal tear, early (<250 days) or delayed (>500 days) return to sports or activity, and use of allograft. Significant predictors for TKA included older age, increased pain scores, total number of arthroscopic surgeries, high-demand activity/occupation, hypermobility, higher body mass index, systemic inflammatory disease, increased time to surgery, early (<250 days) or delayed (>500 days) return to sports or activity, and midsubstance tears. The Brier score over time revealed that RSF models outperformed traditional Kaplan-Meier estimators. Conclusion: Machine learning survival models were used to reliably identify patients at risk of developing symptomatic PTOA, and these models consistently outperformed traditional Kaplan-Meier estimators. Strong predictors for the development of PTOA after ACLR included increased pain scores at injury and postoperative visit, older age at injury, total number of arthroscopic procedures, positive postoperative pivot-shift test, and secondary meniscal tear.

Abstract Death rates from primary liver cancer (hepatocellular carcinoma [HCC]) have continued to rise in the United States over the recent decades despite the availability of an increasing range of treatment modalities, including new systemic therapies. Prognosis is strongly associated with tumor stage at diagnosis; however, most cases of HCC are diagnosed beyond an early stage. This lack of early detection has contributed to low survival rates. Professional society guidelines recommend semiannual ultrasound-based HCC screening for at-risk populations, yet HCC surveillance continues to be underused in clinical practice. On April 28, 2022, the Hepatitis B Foundation convened a workshop to discuss the most pressing challenges and barriers to early HCC detection and the need to better leverage existing and emerging tools and technologies that could improve HCC screening and early detection. In this commentary, we summarize technical, patient-level, provider-level, and system-level challenges and opportunities to improve processes and outcomes across the HCC screening continuum. We highlight promising approaches to HCC risk stratification and screening, including new biomarkers, advanced imaging incorporating artificial intelligence, and algorithms for risk stratification. Workshop participants emphasized that action to improve early detection and reduce HCC mortality is urgently needed, noting concern that many of the challenges we face today are the same or similar to those faced a decade ago and that HCC mortality rates have not meaningfully improved. Increasing the uptake of HCC screening was identified as a short-term priority while developing and validating better screening tests and risk-appropriate surveillance strategies.

Abstract Introduction Historical reservations regarding stereotactic radiosurgery (SRS) for small-cell lung cancer (SCLC) brain metastases include concerns for short-interval and diffuse central nervous system (CNS) progression, poor prognoses, and increased neurological mortality specific to SCLC histology. We compared SRS outcomes for SCLC and non-small cell lung cancer (NSCLC) where SRS is well established. Methods Multicenter first-line SRS outcomes for SCLC and NSCLC from 2000 to 2022 were retrospectively collected (n = 892 SCLC, n = 4785 NSCLC). Data from the prospective Japanese Leksell Gamma Knife Society (JLGK0901) clinical trial of first-line SRS were analyzed as a comparison cohort (n = 98 SCLC, n = 814 NSCLC). Overall survival (OS) and CNS progression were analyzed using Cox proportional hazard and Fine-Gray models, respectively, with multivariable adjustment for cofactors including age, sex, performance status, year, extracranial disease status, and brain metastasis number and volume. Mutation-stratified analyses were performed in propensity score–matched retrospective cohorts of epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) positive NSCLC, mutation-negative NSCLC, and SCLC. Results OS was superior for patients with NSCLC compared to SCLC in the retrospective dataset (median OS = 10.5 vs 8.6 months; P &lt; .001) and in the JLGK0901 dataset. Hazard estimates for first CNS progression favoring NSCLC were similar in both datasets but reached statistical significance in the retrospective dataset only (multivariable hazard ratio = 0.82, 95% confidence interval = 0.73 to 0.92, P = .001). In the propensity score–matched cohorts, there were continued OS advantages for NSCLC patients (median OS = 23.7 [EGFR and ALK positive NSCLC] vs 13.6 [mutation-negative NSCLC] vs 10.4 months [SCLC], pairwise P values &lt; 0.001), but no statistically significant differences in CNS progression were observed in the matched cohorts. Neurological mortality and number of lesions at CNS progression were similar for NSCLC and SCLC patients. Leptomeningeal progression was increased in patients with NSCLC compared to SCLC in the retrospective dataset only (multivariable hazard ratio = 1.61, 95% confidence interval = 1.14 to 2.26, P = .007). Conclusions After SRS, SCLC histology was associated with shorter OS compared to NSCLC. CNS progression occurred earlier in SCLC patients overall but was similar in patients matched on baseline factors. SCLC was not associated with increased neurological mortality, number of lesions at CNS progression, or leptomeningeal progression compared to NSCLC. These findings may better inform clinical expectations and individualized decision making regarding SRS for SCLC patients.

Abstract Obesity is a chronic, relapsing, progressive disease of excess adiposity that increases the risk of developing at least 13 types of cancer. This report provides a concise review of the current state of the science regarding metabolic and bariatric surgery and obesity pharmacotherapy related to cancer risk. Meta-analyses of cohort studies report that metabolic and bariatric surgery is independently associated with a lower risk of incident cancer than nonsurgical obesity care. Less is known regarding the cancer-preventive effects of obesity pharmacotherapy. The recent approval and promising pipeline of obesity drugs will provide the opportunity to understand the potential for obesity therapy to emerge as an evidence-based cancer prevention strategy. There are myriad research opportunities to advance our understanding of how metabolic and bariatric surgery and obesity pharmacotherapy may be used for cancer prevention.

PURPOSE Polycythemia vera (PV) is characterized by JAK/STAT activation, thrombotic/hemorrhagic events, systemic symptoms, and disease transformation. In high-risk PV, ruxolitinib controls blood counts and improves symptoms. PATIENTS AND METHODS MAJIC-PV is a randomized phase II trial of ruxolitinib versus best available therapy (BAT) in patients resistant/intolerant to hydroxycarbamide (HC-INT/RES). Primary outcome was complete response (CR) within 1 year. Secondary outcomes included duration of response, event-free survival (EFS), symptom, and molecular response. RESULTS One hundred eighty patients were randomly assigned. CR was achieved in 40 (43%) patients on ruxolitinib versus 23 (26%) on BAT (odds ratio, 2.12; 90% CI, 1.25 to 3.60; P = .02). Duration of CR was superior for ruxolitinib (hazard ratio [HR], 0.38; 95% CI, 0.24 to 0.61; P < .001). Symptom responses were better with ruxolitinib and durable. EFS (major thrombosis, hemorrhage, transformation, and death) was superior for patients attaining CR within 1 year (HR, 0.41; 95% CI, 0.21 to 0.78; P = .01); and those on ruxolitinib (HR, 0.58; 95% CI, 0.35 to 0.94; P = .03). Serial analysis of JAK2V617F variant allele fraction revealed molecular response was more frequent with ruxolitinib and was associated with improved outcomes (progression-free survival [PFS] P = .001, EFS P = .001, overall survival P = .01) and clearance of JAK2V617F stem/progenitor cells. ASXL1 mutations predicted for adverse EFS (HR, 3.02; 95% CI, 1.47 to 6.17; P = .003). The safety profile of ruxolitinib was as previously reported. CONCLUSION The MAJIC-PV study demonstrates ruxolitinib treatment benefits HC-INT/RES PV patients with superior CR, and EFS as well as molecular response; importantly also demonstrating for the first time, to our knowledge, that molecular response is linked to EFS, PFS, and OS.

Abstract Background Producing scholarship in education is essential to the career development of a clinician-educator. Challenges to scholarly production include a lack of resources, time, expertise, and collaborators. Objective To develop communities of practice for education scholarship through an international society to increase community and academic productivity. Methods We developed multi-institutional scholarship pods within the American Thoracic Society through the creation of a working group (2017–2019). Pods met virtually, and meetings were goal focused to advance education scholarship within their area of interest. To understand the impact of these scholarship pods, we surveyed pod leaders and members in 2021 and analyzed the academic productivity of each pod via a survey of pod leaders and a review of the PubMed index. Results Nine pods were created, each with an assigned educational topic. The survey had a response rate of 76.6%. The perceived benefits were the opportunity to meet colleagues with similar interests at other institutions, production of scholarly work, and engagement in new experiences. The main challenges were difficulty finding times to meet because of competing clinical demands and aligning times among pod members. Regarding academic productivity, eight publications, four conference presentations, and one webinar/podcast were produced by six of the nine pods. Conclusion The development of communities of practice resulted in increased multi-site collaboration, with boosted academic productivity as well as an enhanced sense of belonging. Multiple challenges remain but can likely be overcome with accountability, early discussion of roles and expectations, and clear delegation of tasks and authorship.