The limits of relational governance: Sales force strategies in the U.S. medical device industry

Research Summary: We explore how inter-organizational relationships shape firm boundary decisions. Using data on 545 U.S. medical device manufacturers’ product portfolios and sales governance choices (i.e., internal or external sales forces) from 1983 to 1996, we find relational capital between manufacturers and external sales forces influences future firm boundary decisions. Relational capital lowers the likelihood of integrating the sales function, but only when firms remain focused on the same product market. Further, launching an innovative product has a nuanced effect. For firms lacking relational capital, innovation increases the likelihood of sales integration. This pattern reverses as relational capital accumulates, but only when innovations are in the firm’s existing focal product market. Our findings suggest important limits on the effect of relational governance on firm strategy. Managerial Abstract: Choosing between in-house or external sales is a key strategic decision. In the medical device industry, this decision is particularly important because sales people are conduits between R&D and customers. For firms who initially choose external sales, the tradeoff between maintaining existing links (via external sales) and developing new, direct relationships (by bringing sales in-house) can change significantly as product portfolios change. Analyzing 545 U.S. medical device manufacturers from 1983 to 1996, we find that existing relationships with external sales forces reduce the likelihood of bringing sales in-house, but only when firms remain in the same product market, such as orthopedic implants. When firms launch products in new markets, especially innovations, they are more likely to bring sales in-house

The self-report version and digital format of the COVID-19 Yorkshire Rehabilitation Scale (C19-YRS) for Long Covid or Post-COVID syndrome assessment and monitoring

The C19-YRS was the first scale reported in the literature for patient assessment and monitoring in Long Covid or Post-COVID syndrome. The scale has demonstrated content validity in a previous COVID-19 follow-up study. The growing number of patients with Post-COVID syndrome required the development of a self-report version (and a digital format) so that the scale can be completed by patients themselves. Individuals with Long Covid and clinicians providing care were involved in iterative changes to the scale. The self-report version of the scale captures symptom severity, functional disability and global health status. The C19-YRS digital format comprises a smartphone application for the patient and a web portal for the clinician to assess, triage and monitor patients remotely. The items have been shown to span all the components of the WHO ICF Framework for health condition

The COVID‐19 Yorkshire Rehabilitation Scale (C19‐YRS): application and psychometric analysis in a post‐COVID‐19 syndrome cohort

As our understanding of the nature and prevalence of post-coronavirus disease 2019 (COVID-19) syndrome (PCS) is increasing, a measure of the impact of COVID-19 could provide valuable insights into patients' perceptions in clinical trials and epidemiological studies as well as routine clinical practice. To evaluate the clinical usefulness and psychometric properties of the COVID-19 Yorkshire Rehabilitation Scale (C19-YRS) in patients with PCS, a prospective, observational study of 187 consecutive patients attending a post-COVID-19 rehabilitation clinic was conducted. The C19-YRS was used to record patients' symptoms, functioning, and disability. A global health question was used to measure the overall impact of PCS on health. Classical psychometric methods (data quality, scaling assumptions, targeting, reliability, and validity) were used to assess the C19-YRS. For the total group, missing data were low, scaling and targeting assumptions were satisfied, and internal consistency was high (Cronbach's α = 0.891). Relationships between the overall perception of health and patients' reports of symptoms, functioning, and disability demonstrated good concordance. This is the first study to examine the psychometric properties of an outcome measure in patients with PCS. In this sample of patients, the C19-YRS was clinically useful and satisfied standard psychometric criteria, providing preliminary evidence of its suitability as a measure of PCS

The modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) patient-reported outcome measure for Long Covid or Post-COVID-19 syndrome

Background The C19-YRS is the literature's first condition-specific, validated scale for patient assessment and monitoring in Post-COVID-19 syndrome (PCS). The 22-item scale's subscales (scores) are symptom severity (0–100), functional disability (0–50), additional symptoms (0–60), and overall health (0–10). Objectives This study aimed to test the scale's psychometric properties using Rasch analysis and modify the scale based on analysis findings, emerging information on essential PCS symptoms, and feedback from a working group of patients and professionals. Methods Data from 370 PCS patients were assessed using a Rasch Measurement Theory framework to test model fit, local dependency, response category functioning, differential item functioning, targeting, reliability, and unidimensionality. The working group undertook iterative changes to the scale based on the psychometric results and including essential symptoms. Results Symptom severity and functional disability subscales showed good targeting and reliability. Post hoc rescoring suggested that a 4-point response category structure would be more appropriate than an 11-point response for both subscales. Symptoms with binary responses were placed in the other symptoms subscale. The overall health single-item subscale remained unchanged. Conclusion A 17-item C19-YRSm was developed with subscales (scores): symptom severity (0–30), functional disability (0–15), other symptoms (0–25), and overall health (0–10)

Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer

BACKGROUND The recurrence score based on the 21-gene breast cancer assay predicts chemotherapy benefit if it is high and a low risk of recurrence in the absence of chemotherapy if it is low; however, there is uncertainty about the benefit of chemotherapy for most patients, who have a midrange score. METHODS We performed a prospective trial involving 10,273 women with hormone-receptor–positive, human epidermal growth factor receptor 2 (HER2)–negative, axillary node–negative breast cancer. Of the 9719 eligible patients with follow-up information, 6711 (69%) had a midrange recurrence score of 11 to 25 and were randomly assigned to receive either chemoendocrine therapy or endocrine therapy alone. The trial was designed to show noninferiority of endocrine therapy alone for invasive disease–free survival (defined as freedom from invasive disease recurrence, second primary cancer, or death). RESULTS Endocrine therapy was noninferior to chemoendocrine therapy in the analysis of invasive disease–free survival (hazard ratio for invasive disease recurrence, second primary cancer, or death [endocrine vs. chemoendocrine therapy], 1.08; 95% confidence interval, 0.94 to 1.24; P=0.26). At 9 years, the two treatment groups had similar rates of invasive disease–free survival (83.3% in the endocrine-therapy group and 84.3% in the chemoendocrine-therapy group), freedom from disease recurrence at a distant site (94.5% and 95.0%) or at a distant or local–regional site (92.2% and 92.9%), and overall survival (93.9% and 93.8%). The chemotherapy benefit for invasive disease–free survival varied with the combination of recurrence score and age (P=0.004), with some benefit of chemotherapy found in women 50 years of age or younger with a recurrence score of 16 to 25. CONCLUSIONS Adjuvant endocrine therapy and chemoendocrine therapy had similar efficacy in women with hormone-receptor–positive, HER2-negative, axillary node–negative breast cancer who had a midrange 21-gene recurrence score, although some benefit of chemotherapy was found in some women 50 years of age or younger

Clinical and Genomic Risk to Guide the Use of Adjuvant Therapy for Breast Cancer

BACKGROUND The use of adjuvant chemotherapy in patients with breast cancer may be guided by clinicopathological factors and a score based on a 21-gene assay to determine the risk of recurrence. Whether the level of clinical risk of breast cancer recurrence adds prognostic information to the recurrence score is not known. METHODS We performed a prospective trial involving 9427 women with hormone-receptor–positive, human epidermal growth factor receptor 2–negative, axillary node–negative breast cancer, in whom an assay of 21 genes had been performed, and we classified the clinical risk of recurrence of breast cancer as low or high on the basis of the tumor size and histologic grade. The effect of clinical risk was evaluated by calculating hazard ratios for distant recurrence with the use of Cox proportional-hazards models. The initial endocrine therapy was tamoxifen alone in the majority of the premenopausal women who were 50 years of age or younger. RESULTS The level of clinical risk was prognostic of distant recurrence in women with an intermediate 21-gene recurrence score of 11 to 25 (on a scale of 0 to 100, with higher scores indicating a worse prognosis or a greater potential benefit from chemotherapy) who were randomly assigned to endocrine therapy (hazard ratio for the comparison of high vs. low clinical risk, 2.73; 95% confidence interval [CI], 1.93 to 3.87) or to chemotherapy plus endocrine (chemoendocrine) therapy (hazard ratio, 2.41; 95% CI, 1.66 to 3.48) and in women with a high recurrence score (a score of 26 to 100), all of whom were assigned to chemoendocrine therapy (hazard ratio, 3.17; 95% CI, 1.94 to 5.19). Among women who were 50 years of age or younger who had received endocrine therapy alone, the estimated (±SE) rate of distant recurrence at 9 years was less than 5% (≤1.8±0.9%) with a low recurrence score (a score of 0 to 10), irrespective of clinical risk, and 4.7±1.0% with an intermediate recurrence score and low clinical risk. In this age group, the estimated distant recurrence at 9 years exceeded 10% among women with a high clinical risk and an intermediate recurrence score who received endocrine therapy alone (12.3±2.4%) and among those with a high recurrence score who received chemoendocrine therapy (15.2±3.3%). CONCLUSIONS Clinical-risk stratification provided prognostic information that, when added to the 21-gene recurrence score, could be used to identify premenopausal women who could benefit from more effective therapy

A Dynamical Systems Model for Combinatorial Cancer Therapy Enhances Oncolytic Adenovirus Efficacy by MEK-Inhibition

Oncolytic adenoviruses, such as ONYX-015, have been tested in clinical trials for currently untreatable tumors, but have yet to demonstrate adequate therapeutic efficacy. The extent to which viruses infect targeted cells determines the efficacy of this approach but many tumors down-regulate the Coxsackievirus and Adenovirus Receptor (CAR), rendering them less susceptible to infection. Disrupting MAPK pathway signaling by pharmacological inhibition of MEK up-regulates CAR expression, offering possible enhanced adenovirus infection. MEK inhibition, however, interferes with adenovirus replication due to resulting G1-phase cell cycle arrest. Therefore, enhanced efficacy will depend on treatment protocols that productively balance these competing effects. Predictive understanding of how to attain and enhance therapeutic efficacy of combinatorial treatment is difficult since the effects of MEK inhibitors, in conjunction with adenovirus/cell interactions, are complex nonlinear dynamic processes. We investigated combinatorial treatment strategies using a mathematical model that predicts the impact of MEK inhibition on tumor cell proliferation, ONYX-015 infection, and oncolysis. Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies. Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study. Further analysis revealed that a CAR-independent mechanism may be responsible for amplified virus production and cell death. We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis. Enhanced oncolytic therapy has the potential to dramatically improve non-surgical cancer treatment, especially in locally advanced or metastatic cases where treatment options remain limited.National Institutes of Health (U.S.) (Grant R01 CA118545)National Institutes of Health (U.S.) (Grant R01 CA095701)National Institutes of Health (U.S.) (Grant U54 CA11297)National Institutes of Health (U.S.) (Grant U54-CA112967

Turning high-throughput structural biology into predictive inhibitor design

A common challenge in drug design pertains to finding chemical modifications to a ligand that increases its affinity to the target protein. An underutilized advance is the increase in structural biology throughput, which has progressed from an artisanal endeavor to a monthly throughput of hundreds of different ligands against a protein in modern synchrotrons. However, the missing piece is a framework that turns high-throughput crystallography data into predictive models for ligand design. Here, we designed a simple machine learning approach that predicts protein–ligand affinity from experimental structures of diverse ligands against a single protein paired with biochemical measurements. Our key insight is using physics-based energy descriptors to represent protein–ligand complexes and a learning-to-rank approach that infers the relevant differences between binding modes. We ran a high-throughput crystallography campaign against the SARS-CoV-2 main protease (MPro), obtaining parallel measurements of over 200 protein–ligand complexes and their binding activities. This allows us to design one-step library syntheses which improved the potency of two distinct micromolar hits by over 10-fold, arriving at a noncovalent and nonpeptidomimetic inhibitor with 120 nM antiviral efficacy. Crucially, our approach successfully extends ligands to unexplored regions of the binding pocket, executing large and fruitful moves in chemical space with simple chemistry

Prospective Validation of a 21-Gene Expression Assay in Breast Cancer

Prior studies with the use of a prospective–retrospective design including archival tumor samples have shown that gene-expression assays provide clinically useful prognostic information. However, a prospectively conducted study in a uniformly treated population provides the highest level of evidence supporting the clinical validity and usefulness of a biomarker

Clinical Characteristics, Racial Inequities, and Outcomes in Patients with Breast Cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) Cohort Study

BACKGROUND: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. METHODS: This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity. RESULTS: 1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32-1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70-6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83-12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63-3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20-2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66-3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89-22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status. CONCLUSIONS: Using one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients. FUNDING: This study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication. CLINICAL TRIAL NUMBER: CCC19 registry is registered on ClinicalTrials.gov, NCT04354701