Opioid-Free Discharge After Pancreatic Resection Through a Learning Health System Paradigm.

Importance: Postoperative opioid overprescribing leads to persistent opioid use and excess pills at risk for misuse and diversion. A learning health system paradigm using risk-stratified pancreatectomy clinical pathways (RSPCPs) may lead to reduction in inpatient and discharge opioid volume. Objective: To analyze the outcomes of 2 iterative RSPCP updates on inpatient and discharge opioid volumes. Design, Setting, and Participants: This cohort study included 832 consecutive adult patients at an urban comprehensive cancer center who underwent pancreatic resection between October 2016 and April 2022, comprising 3 sequential pathway cohorts (version [V] 1, October 1, 2016, to January 31, 2019 [n = 363]; V2, February 1, 2019, to October 31, 2020 [n = 229]; V3, November 1, 2020, to April 30, 2022 [n = 240]). Exposures: After V1 of the pathway established a baseline and reduced length of stay (n = 363), V2 (n = 229) updated patient and surgeon education handouts, limited intravenous opioids, suggested a 3-drug (acetaminophen, celecoxib, methocarbamol) nonopioid bundle, and implemented the 5×-multiplier (last 24-hour oral morphine equivalents [OME] multiplied by 5) to calculate discharge volume. Pathway version 3 (n = 240) required the nonopioid bundle as default in the recovery room and scheduled conversion to oral medications on postoperative day 1. Main Outcomes and Measures: Inpatient and discharge opioid volume in OME across the 3 RSPCPs were compared using nonparametric testing and trend analyses. Results: A total of 832 consecutive patients (median [IQR] age, 65 [56-72] years; 410 female [49.3%] and 422 male [50.7%]) underwent 541 pancreatoduodenectomies, 285 distal pancreatectomies, and 6 other pancreatectomies. Early nonopioid bundle administration increased from V1 (acetaminophen, 320 patients [88.2%]; celecoxib or anti-inflammatory, 98 patients [27.0%]; methocarbamol, 267 patients [73.6%]) to V3 (236 patients [98.3%], 163 patients [67.9%], and 238 patients [99.2%], respectively; P < .001). Total inpatient OME decreased from a median 290 mg (IQR, 157-468 mg) in V1 to 184 mg (IQR, 103-311 mg) in V2 to 129 mg (IQR, 75-206 mg) in V3 (P < .001). Discharge OME decreased from a median 150 mg (IQR, 100-225 mg) in V1 to 25 mg (IQR, 0-100 mg) in V2 to 0 mg (IQR, 0-50 mg) in V3 (P < .001). The percentage of patients discharged opioid free increased from 7.2% (26 of 363) in V1 to 52.5% (126 of 240) in V3 (P < .001), with 187 of 240 (77.9%) in V3 discharged with 50 mg OME or less. Median pain scores remained 3 or lower in all cohorts, with no differences in postdischarge refill requests. A subgroup analysis separating open and minimally invasive surgical cases showed similar results in both groups. Conclusions and Relevance: In this cohort study, the median total inpatient OME was halved and median discharge OME reduced to zero in association with a learning health system model of iterative opioid reduction that is freely adaptable by other hospitals. These findings suggest that opioid-free discharge after pancreatectomy and other major cancer operations is realistic and feasible with this no-cost blueprint.

Docking and virtual screening to identify PKC agonists: potentials in anticancer therapeutics.

Protein kinase C (PKC) is down-stream to most of the G-protein coupled receptor or tyrosine kinase receptors mediated signaling events from the cell surface. PKC C1 domain has a hydrophobic region with a polar groove to facilitate 1,2-diacyl-glycerol (DAG) binding or other agonist molecule for PKC activation. Post activation, a partial or complete blocking of hydrophilic groove makes the DAG binding site completely hydrophobic and facilitates easier penetration of the PKC into the membrane. Phorbol ester, a strong PKC agonist, uses this mechanism to induce tumor formation. A total of 300 heterocyclic compounds with 70% similarity to phorbol 12-myristate 13-acetate (PMA) were selected, and virtual docking was performed with PKC-α as target. An initial screening indicated that most of the molecules fit well into the C1 domain and had better binding energy than PMA. Further analysis in a PMA competition experiment identified five molecules, Zc 67913417, Zc 68601770, Zc 25726447, Zc 35376386 and Zc 49785214 as potent PKC agonists. In addition, as these compounds showed better binding than PMA, more interaction with PKC residues (hydrogen bonding and hydrophobic), and the top five hit molecules was potent enough to abolish carcinogenic effects of PMA. Searching the top heterocyclic compounds into the drug database gave a number of approved drugs. Testing two candidate drugs, nandrolone decanoate and budesonide, reduced cellular viability of HT1080 in a dose-dependent manner with an IC50 values of 96.8 nM and 200nM respectively. An in silico toxicity analysis indicated that top hit molecules are non-toxic, non-mutagenic in cellular and bacterial system, and have no tumorigenic potentials in a single cell or animal model. Hence, a virtual screening, agonist competition assay, and in silico toxicity assessment allowed us to identify five new PKC agonist molecules for future drug discovery against cancer.