Evaluating the fairness and accuracy of machine learning-based predictions of clinical outcomes after anatomic and reverse total shoulder arthroplasty.

BACKGROUND: Machine learning (ML)-based clinical decision support tools (CDSTs) make personalized predictions for different treatments; by comparing predictions of multiple treatments, these tools can be used to optimize decision making for a particular patient. However, CDST prediction accuracy varies for different patients and also for different treatment options. If these differences are sufficiently large and consistent for a particular subcohort of patients, then that bias may result in those patients not receiving a particular treatment. Such level of bias would deem the CDST "unfair." The purpose of this study is to evaluate the "fairness" of ML CDST-based clinical outcomes predictions after anatomic (aTSA) and reverse total shoulder arthroplasty (rTSA) for patients of different demographic attributes. METHODS: Clinical data from 8280 shoulder arthroplasty patients with 19,249 postoperative visits was used to evaluate the prediction fairness and accuracy associated with the following patient demographic attributes: ethnicity, sex, and age at the time of surgery. Performance of clinical outcome and range of motion regression predictions were quantified by the mean absolute error (MAE) and performance of minimal clinically important difference (MCID) and substantial clinical benefit classification predictions were quantified by accuracy, sensitivity, and the F1 score. Fairness of classification predictions leveraged the "four-fifths" legal guideline from the US Equal Employment Opportunity Commission and fairness of regression predictions leveraged established MCID thresholds associated with each outcome measure. RESULTS: For both aTSA and rTSA clinical outcome predictions, only minor differences in MAE were observed between patients of different ethnicity, sex, and age. Evaluation of prediction fairness demonstrated that 0 of 486 MCID (0%) and only 3 of 486 substantial clinical benefit (0.6%) classification predictions were outside the 20% fairness boundary and only 14 of 972 (1.4%) regression predictions were outside of the MCID fairness boundary. Hispanic and Black patients were more likely to have ML predictions out of fairness tolerance for aTSA and rTSA. Additionally, patients <60 years old were more likely to have ML predictions out of fairness tolerance for rTSA. No disparate predictions were identified for sex and no disparate regression predictions were observed for forward elevation, internal rotation score, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form score, or global shoulder function. CONCLUSION: The ML algorithms analyzed in this study accurately predict clinical outcomes after aTSA and rTSA for patients of different ethnicity, sex, and age, where only 1.4% of regression predictions and only 0.3% of classification predictions were out of fairness tolerance using the proposed fairness evaluation method and acceptance criteria. Future work is required to externally validate these ML algorithms to ensure they are equally accurate for all legally protected patient groups.

Turning down the heat: The case for mild hyperthermia and thermosensitive liposomes.

"A single disappointing study does not mean an end to the future of ThermoDox®", writes Michael Tardugno (CEO of Celsion Corporation), after announcing the termination of Celsion's second Phase III clinical trial. The OPTIMA trial, as it was known, evaluated their thermosensitive liposome (TSL) formulation of doxorubicin (ThermoDox®) in combination with radiofrequency ablation for the treatment of hepatocellular carcinoma (HCC). The purpose of this perspective is to review the case of ThermoDox and to address questions related to its clinical translation. Specifically, what has prevented the clinical translation of this once highly regarded breakthrough technology? Is this the end of TSLs? What can we learn from the challenges faced in the clinical development of this multi-modal therapy? As formulation scientists working in the field, we continue to believe that heat-triggered drug delivery platforms have tremendous potential as chemotherapy. Herein, we highlight potential limitations in the design of many of the Thermodox clinical trials, and we propose that despite these setbacks, TSLs have the potential to become an effective component of cancer therapy.

Using machine learning to predict internal rotation after anatomic and reverse total shoulder arthroplasty.

BACKGROUND: Improvement in internal rotation (IR) after anatomic (aTSA) and reverse (rTSA) total shoulder arthroplasty is difficult to predict, with rTSA patients experiencing greater variability and more limited IR improvements than aTSA patients. The purpose of this study is to quantify and compare the IR score for aTSA and rTSA patients and create supervised machine learning that predicts IR after aTSA and rTSA at multiple postoperative time points. METHODS: Clinical data from 2270 aTSA and 4198 rTSA patients were analyzed using 3 supervised machine learning techniques to create predictive models for internal rotation as measured by the IR score at 6 postoperative time points. Predictions were performed using the full input feature set and 2 minimal input feature sets. The mean absolute error (MAE) quantified the difference between actual and predicted IR scores for each model at each time point. The predictive accuracy of the XGBoost algorithm was also quantified by its ability to distinguish which patients would achieve clinical improvement greater than the minimal clinically important difference (MCID) and substantial clinical benefit (SCB) patient satisfaction thresholds for IR score at 2-3 years after surgery. RESULTS: rTSA patients had significantly lower mean IR scores and significantly less mean IR score improvement than aTSA patients at each postoperative time point. Both aTSA and rTSA patients experienced significant improvements in their ability to perform activities of daily living (ADLs); however, aTSA patients were significantly more likely to perform these ADLs. Using a minimal feature set of preoperative inputs, our machine learning algorithms had equivalent accuracy when predicting IR score for both aTSA (0.92-1.18 MAE) and rTSA (1.03-1.25 MAE) from 3 months to >5 years after surgery. Furthermore, these predictive algorithms identified with 90% accuracy for aTSA and 85% accuracy for rTSA which patients will achieve MCID IR score improvement and predicted with 85% accuracy for aTSA patients and 77% accuracy for rTSA which patients will achieve SCB IR score improvement at 2-3 years after surgery. DISCUSSION: Our machine learning study demonstrates that active internal rotation can be accurately predicted after aTSA and rTSA at multiple postoperative time points using a minimal feature set of preoperative inputs. These predictive algorithms accurately identified which patients will, and will not, achieve clinical improvement in IR score that exceeds the MCID and SCB patient satisfaction thresholds.

Life-Threatening Bleeding in Children: A Prospective Observational Study.

OBJECTIVES: The purpose of our study was to describe children with life-threatening bleeding. DESIGN: We conducted a prospective observational study of children with life-threatening bleeding events. SETTING: Twenty-four childrens hospitals in the United States, Canada, and Italy participated. SUBJECTS: Children 0-17 years old who received greater than 40 mL/kg total blood products over 6 hours or were transfused under massive transfusion protocol were included. INTERVENTIONS: Children were compared according bleeding etiology: trauma, operative, or medical. MEASUREMENTS AND MAIN RESULTS: Patient characteristics, therapies administered, and clinical outcomes were analyzed. Among 449 enrolled children, 55.0% were male, and the median age was 7.3 years. Bleeding etiology was 46.1% trauma, 34.1% operative, and 19.8% medical. Prior to the life-threatening bleeding event, most had age-adjusted hypotension (61.2%), and 25% were hypothermic. Children with medical bleeding had higher median Pediatric Risk of Mortality scores (18) compared with children with trauma (11) and operative bleeding (12). Median Glasgow Coma Scale scores were lower for children with trauma (3) compared with operative (14) or medical bleeding (10.5). Median time from bleeding onset to first transfusion was 8 minutes for RBCs, 34 minutes for plasma, and 42 minutes for platelets. Postevent acute respiratory distress syndrome (20.3%) and acute kidney injury (18.5%) were common. Twenty-eight-day mortality was 37.5% and higher among children with medical bleeding (65.2%) compared with trauma (36.1%) and operative (23.8%). There were 82 hemorrhage deaths; 65.8% occurred by 6 hours and 86.5% by 24 hours. CONCLUSIONS: Patient characteristics and outcomes among children with life-threatening bleeding varied by cause of bleeding. Mortality was high, and death from hemorrhage in this population occurred rapidly.

Assessment of a liposomal CT/optical contrast agent for image-guided head and neck surgery.

This study evaluates a long-acting liposomal fluorescence / CT dual-modality contrast agent (CF800) in head and neck cancer to enhance intraoperative tumor demarcation with fluorescence imaging and cone-beam computed tomography (CBCT). CF800 was administered to 12 buccal cancer-bearing rabbits. Imaging was acquired at regular time points to quantify time-dependent contrast enhancement. Surgery was performed 5-7 days after, with intraoperative near-infrared fluorescence endoscopy and CBCT, followed by histological and ex-vivo fluorescence assessment. Tumor enhancement on CT was significant at 24, 96 and 120 hours. Volumetric analysis of tumor segmentation showed high correlation between CBCT and micro-CT. Fluorescence signal was apparent in both ex-vivo and in-vivo imaging. Histological correlation showed [100%] specificity for primary tumor. Sensitivity and specificity of CF800 in detecting nodal involvement require further investigation.CF800 is long acting and has dual function for CT and fluorescence contrast, making it an excellent candidate for image-guided surgery.

Functionalization of Cellulose Nanocrystals with POEGMA Copolymers via Copper-Catalyzed Azide-Alkyne Cycloaddition for Potential Drug-Delivery Applications.

Elongated colloidal nanoparticles (NPs) have significant potential for drug delivery and imaging applications in cancer therapy, but progress depends on developing a deeper understanding of how their physicochemical properties affect their interactions with cells and with tumors. Cellulose nanocrystals (CNCs) are biocompatible, rodlike colloids that are broadly surface-functionalizable, making them interesting as modular drug carriers. In this report, we describe the attachment of a statistical copolymer containing oligoethylene glycol methacrylate (OEGMA; Mn ≈ 500 Da) and small amounts of aminopropylmethacrylamide (APMA) to CNCs. Here, the copolymer is designed to serve as a "stealth" corona to minimize protein adsorption, and the amino groups provide functionality for the attachment of diagnostic or therapeutic moieties. The corona polymer with a terminal azide group was synthesized by atom transfer radical polymerization using tert-butyloxycarbonyl (tBoc)-protected APMA as the comonomer. A key step in this synthesis was the grafting of acetylene groups to the CNC surface via a reaction with NaOH plus propargyl bromide in aqueous dimethyl sulfoxide. The copolymer was attached to the CNCs using copper-catalyzed azide-alkyne cycloaddition (CuAAC) "click" chemistry. By determining the mean number of amino groups per copolymer and amino group content of the CNC sample, we were able to infer that there were on average ca. 300 polymer molecules per CNC. Preliminary evaluation in a human ovarian cancer cell line (HEYA8) and a human breast cancer cell line (MDA-MB-436) demonstrated that these CNCs are nontoxic. We also assessed the cellular uptake of these CNC NPs in the same two cell lines using flow cytometry and distinguished between NPs being internalized by the cell or surface-bound using a trypan blue quenching experiment. These results provide support for applications of polymer-coated CNCs in medicine and are encouraging for further studies in vitro and in vivo to evaluate their potential as drug-delivery vehicles.

Dual-Targeted Delivery of Nanoparticles Encapsulating Paclitaxel and Everolimus: a Novel Strategy to Overcome Breast Cancer Receptor Heterogeneity.

PURPOSE: The intratumoral heterogeneity observed in breast cancer (BC), in particular with regard to cell surface receptor expression, can hinder the success of many targeted cancer therapies. The development of novel therapeutic agents that target more than one receptor can overcome this inherent property of tumors and can facilitate their selective internalization in cancer cells. The goal of this study is to develop a drug combination-loaded nanoparticle (NP) formulation that is actively-targeted to HER2 and EGFR receptors on BC cells. METHODS: A polymeric NP formulation was prepared which co-encapsulated a synergistic combination of the chemotherapeutic agent, paclitaxel (PTX), and the mTOR inhibitor, everolimus (EVER), and is targeted to HER2 and EGFR receptors on BC cells using antibody Fab fragments as the targeting moieties. The physicochemical characteristics of the dual-targeted formulation (Dual-NP) were evaluated, along with its cytotoxic profile (in both, monolayer and 3D BC models), as well as the degree of cellular uptake in HER2high/EGFRmod and HER2neg/EGFRlow BC cells. RESULTS: Dual-NPs were found to have significantly higher cytotoxicity relative to HER2 mono-targeted (T-NPs) and untargeted NPs (UT-NPs) in HER2high/EGFRmod monolayer BC cells after 72 h exposure, while no significant difference was observed in HER2neg/EGFRlow cells. However, in the HER2high/EGFRmod spheroids, the cytotoxicity of Dual-NPs was comparable to that of T-NPs. This was thought to be attributed to the previously reported downregulation of EGFR in 3D in comparison to 2D BC models. Dual-NPs had significantly higher cellular uptake relative to UT-NPs and T-NPs in HER2high/EGFRmod BC cells after 24 h exposure, whereas in the HER2neg/EGFRlow cells, the increase in cellular uptake of the Dual-NPs was not as high as the level achieved in the HER2high/EGFRmod cells. Blocking HER2 and EGFR significantly reduced the uptake of T-NPs and Dual-NPs in the HER2high/EGFRmod BC cells, demonstrating specific binding to both EGFR and HER2. CONCLUSIONS: The dual-targeting strategy developed in this study in conjunction with a potentially promising delivery vector for a synergistic combination therapy can overcome receptor heterogeneity, yielding significant improvements in the cytotoxicity and cellular uptake in BC cells.

Potential Limitations of Bioluminescent Xenograft Mouse Models: A Systematic Review.

PURPOSE: Bioluminescent imaging (BLI) is a versatile technique that offers non-invasive and real-time monitoring of tumor development in preclinical cancer research. However, the technique may be limited by several factors that can lead to misinterpretation of the data. This review aimed to investigate the validity of current BLI tumor models and provide recommendations for future model development. METHODS: Two major databases, MedLine and EMBASE, were searched from inception to July 2018 inclusively. Studies utilizing mouse xenograft models with demonstration of linear correlations between bioluminescent signal and tumor burden were included. Coefficients of correlation and determination were extracted along with data relating to animal model parameters. RESULTS: 116 studies were included for analysis. It was found that the majority of models demonstrate good correlation regardless of the model type. Selection of a single cell clone with highest luciferase expression resulted in a significantly better correlation. Lastly, appropriate tumor measurement techniques should be utilized when validating the BLI model. CONCLUSIONS: In general, BLI remains a valid tool for pre-clinical assessment of tumor burden. While no single factor may be identified as a general limitation, data should be interpreted with caution.

Short-Term Adverse Outcomes Associated With Hypoglycemia in Critically Ill Children.

OBJECTIVES: Previous studies report worse short-term outcomes with hypoglycemia in critically ill children. These studies relied on intermittent blood glucose measurements, which may have introduced detection bias. We analyzed data from the Heart And Lung Failure-Pediatric INsulin Titration trial to determine the association of hypoglycemia with adverse short-term outcomes in critically ill children. DESIGN: Nested case-control study. SETTING: Thirty-five PICUs. A computerized algorithm that guided the timing of blood glucose measurements and titration of insulin infusion, continuous glucose monitors, and standardized glucose infusion rates were used to minimize hypoglycemia. PATIENTS: Nondiabetic children with cardiovascular and/or respiratory failure and hyperglycemia. Cases were children with any hypoglycemia (blood glucose < 60 mg/dL), whereas controls were children without hypoglycemia. Each case was matched with up to four unique controls according to age group, study day, and severity of illness. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 112 (16.0%) of 698 children who received the Heart And Lung Failure-Pediatric INsulin Titration protocol developed hypoglycemia, including 25 (3.6%) who developed severe hypoglycemia (blood glucose < 40 mg/dL). Of these, 110 cases were matched to 427 controls. Hypoglycemia was associated with fewer ICU-free days (median, 15.3 vs 20.2 d; p = 0.04) and fewer hospital-free days (0 vs 7 d; p = 0.01) through day 28. Ventilator-free days through day 28 and mortality at 28 and 90 days did not differ between groups. More children with insulin-induced versus noninsulin-induced hypoglycemia had zero ICU-free days (35.8% vs 20.9%; p = 0.008). Outcomes did not differ between children with severe versus nonsevere hypoglycemia or those with recurrent versus isolated hypoglycemia. CONCLUSIONS: When a computerized algorithm, continuous glucose monitors and standardized glucose infusion rates were used to manage hyperglycemia in critically ill children with cardiovascular and/or respiratory failure, severe hypoglycemia (blood glucose < 40 mg/dL) was uncommon, but any hypoglycemia (blood glucose < 60 mg/dL) remained common and was associated with worse short-term outcomes.

Development of a Bioluminescent BRCA1-Deficient Xenograft Model of Disseminated, High-Grade Serous Ovarian Cancer.

Successful translation of preclinical data relies on valid and comprehensive animal models. While high-grade serous ovarian cancer (HGSOC) is the most prevalent subtype, the most commonly used ovarian cancer cell lines are not representative of HGSOC. In addition, 50% of ovarian cancer patients present with dysfunctional BRCA1/2, however currently there is a shortage of BRCA-deficient models. By utilizing the OVCAR8 cell line, which contains a hypermethylated BRCA1 promoter, the aim of the current study was to establish and characterize an animal model for BRCA-deficient HGSOC. Transfection of the luciferase gene to OVCAR8 cells enabled bioluminescent imaging for real-time, non-invasive monitoring of tumor growth. The resulting model was characterized by peritoneal metastasis and ascites formation at late stages of disease. Immunohistochemical staining revealed high-grade serous histology in all resected tumor nodules. Immunoblotting and qPCR analysis demonstrated BRCA1 deficiency was maintained in vivo. Moderate to strong correlations were observed between bioluminescent signal and tumor weight. Lastly, intraperitoneal administration of carboplatin significantly reduced tumor growth as measured by bioluminescence. The current model demonstrated BRCA1 deficiency and a high resemblance of the clinical features of HGSOC. This model may be well-suited for evaluation of therapeutic efficacy in BRCA-deficient HGSOC.

Codelivery of Paclitaxel and Everolimus at the Optimal Synergistic Ratio: A Promising Solution for the Treatment of Breast Cancer.

Clinical studies examining the combination of paclitaxel (PTX) and everolimus (EVER), an mTOR inhibitor, have failed to result in significant improvements in efficacy and toxicity in patients with breast cancer (BC), relative to treatment with PTX alone. These disappointing clinical trial results have been attributed to poorly designed preclinical studies using the combination of PTX and EVER as well as the significantly different pharmacokinetic profiles of the two drugs. In the current work, the potential synergy between PTX and EVER was examined in a panel of six BC cell lines that differ in terms of their molecular subtype and drug sensitivity. Polymeric nanoparticles (NPs) were used to encapsulate PTX and EVER at an optimal synergistic ratio to achieve specific, colocalized delivery of the combination therapy in BC cell lines. Combinations of PTX and EVER (especially at relatively high doses of EVER) resulted in pronounced synergy in all BC cell lines evaluated. The optimal molar ratio of PTX:EVER was determined to be 1:0.5. The combination was delivered to BC cells at the synergistic ratio via encapsulation within polymeric NPs formed from the poly(ethylene glycol)- b-poly(lactide- co-glycolide) (PEG- b-PLGA) copolymer. The NPs had an average diameter of less than 100 nm and were capable of in vitro retention of the encapsulated PTX and EVER at the optimal synergistic molar ratio for over 7 days. Cytotoxicity data demonstrated that PTX+EVER-loaded NPs were significantly less cytotoxic than the free drug combination in MCF-7 and SKBR3 BC cell lines following 72 h, suggesting that PTX+EVER-loaded NPs remain stable and retain the drug combination loaded within the core after 72 h. The uptake of FITC-labeled NPs in SKBR3 cells was evaluated by flow cytometry, with approximately 41% of cells demonstrating detectable fluorescence after 24 h of exposure. The thorough and systematic approach used in this study to determine and evaluate a synergistic PTX:EVER ratio in conjunction with a potentially promising delivery vector for the drug combination could offer a future clinical benefit for patients with BC.

Factors Controlling Drug Release in Cross-linked Poly(valerolactone) Based Matrices.

There is keen interest in the development of biocompatible and biodegradable implantable delivery systems (IDDS) that provide sustained drug release for prolonged periods in humans. These systems have the potential to enhance therapeutic outcomes, reduce systemic toxicity, and improve patient compliance. Herein, we report the preparation and physicochemical characterization of cross-linked polymeric matrices from poly(valerolactone)- co-poly(allyl-δ-valerolactone) (PVL- co-PAVL) copolymers for use in drug delivery. A series of well-defined PVL- co-PAVL copolymers (PDI < 1.5) that vary in terms of MW and AVL content were prepared by ring opening polymerization catalyzed by 1,5,7-triazabicyclo[4.4.0]dec-5-ene. A subsequent cross-linking reaction using 1,6-hexanedithiol led to solid cylindrical amorphous or semicrystalline matrices as potential IDDS. High loading levels (up to 20% (w/w)) of several model drugs that vary in physicochemical properties, including paclitaxel, triamcinolone acetonide and hexacetonide, curcumin, and acetaminophen, were achieved using a postloading method in organic solvent. Drug-IDDS interactions were evaluated via the group contribution method and X-ray diffraction as well as calorimetric, spectroscopic, and microscopic techniques. Results indicate superior drug-matrix compatibility for drugs bearing phenyl groups. In vitro release studies under distinct sink conditions highlight the key factors (i.e., state and loading level of drug, solubility of drug in external media, and composition of release media) that impact drug release.

BRCA Status Does Not Predict Synergism of a Carboplatin and Olaparib Combination in High-Grade Serous Ovarian Cancer Cell Lines.

Over 50% of epithelial ovarian cancers express the BRCAness profile that leads to a dysfunctional homologous recombination repair system. The combination of a dysfunctional homologous recombination repair system and a poly(ADP-ribose) polymerase (PARP) inhibitor results in a synthetic lethal phenotype. The PARP inhibitor olaparib, approved as a monotherapy for patients with a germline BRCA mutation, has shown promising results in preclinical studies when combined with DNA damaging agents, such as carboplatin. However, dose-limiting toxicities have hindered the use of a combination therapy with olaparib in the clinical setting. By concurrent administration of carboplatin and olaparib at various molar ratios of drugs, the aim of this study was to explore the optimal dosing ratio of carboplatin-olaparib combinations in a comprehensive panel of eight BRCA-proficient and -deficient high-grade serous ovarian cancer (HGSOC) cell lines. Overall, synergy was observed in the BRCA1/2-mutated or defective cell lines when olaparib was combined at lower molar ratios of olaparib to carboplatin. Immunostaining of γH2AX foci revealed increased DNA damage as a result of this synergistic drug combination in the UWB1.289 paired cell lines. In vitro activity of the individual agents, carboplatin and olaparib, did not correlate with PARP1 expression in each cell line. Importantly, synergism was also observed in a subset of BRCA wild-type cell lines (OV90 and PEO4) suggesting therapeutic benefits of this combination beyond BRCA-dependent synthetic lethality. The administration of drugs at synergistic ratios has the potential to increase efficacy and reduce toxicity.

Ratio-Dependent Synergism of a Doxorubicin and Olaparib Combination in 2D and Spheroid Models of Ovarian Cancer.

Ovarian cancer is the fourth leading cause of death in women in developed countries. Even though patients with the most lethal form of the disease (HGSOC; high grade serous ovarian cancer) respond well to initial treatment, they often relapse with progressively resistant disease. Inhibitors of the poly(ADP-ribose) polymerase (PARP) enzymes are a relatively new class of molecularly targeted small molecule drugs that show promise in overcoming resistance. The present study explores the combination of a DNA damaging agent, doxorubicin (DOX), with the PARP inhibitor, olaparib (OLP), in order to achieve optimal synergy of both drugs in serous ovarian cancer. This drug combination was evaluated and optimized in 2D monolayers and 3D multicellular tumor spheroids (MCTS) using a genetically and histologically characterized panel of nine OC cell lines with or without BRCA1 or BRCA2 mutations. Combination index (CI) values of DOX and OLP were determined using the Chou and Talalay method. The potency of this drug combination was found to rely heavily on the molar ratios at which the two drugs are combined. In general, MCTS growth inhibition was reflective of the patterns predicted by the CI values obtained in monolayers. Promising combination ratios identified in this study warrant further preclinical and clinical investigation.

Overcoming the Road Blocks: Advancement of Block Copolymer Micelles for Cancer Therapy in the Clinic.

With countless preclinical studies on block copolymer micelles (BCMs) successfully demonstrating the superiority of these advanced drug delivery formulations over conventional formulations, it remains somehow discouraging that only a few have reached clinical evaluation and practice. With a critical eye, this review aims to compare and summarize the preclinical and clinical data available on several BCM formulations and to identify their primary role in drug delivery as "carrier" or "solubilizer". This review focuses on polymeric micelles that have reached clinical evaluation and/or are being pursued commercially. Where available, we aim to compare the pharmacokinetics, toxicity, and efficacy data obtained in preclinical studies to identify the factors that likely played a key role in a decision to move these formulations forward from the bench to a first-in-human trial. Finally, we summarize clinical data obtained to date, where available, and conclude with the impact that each formulation has had on patients in terms of safety and efficacy.

Trends and Patterns of Disparities in Cancer Mortality Among US Counties, 1980-2014.

Introduction: Cancer is a leading cause of morbidity and mortality in the United States and results in a high economic burden. Objective: To estimate age-standardized mortality rates by US county from 29 cancers. Design and Setting: Deidentified death records from the National Center for Health Statistics (NCHS) and population counts from the Census Bureau, the NCHS, and the Human Mortality Database from 1980 to 2014 were used. Validated small area estimation models were used to estimate county-level mortality rates from 29 cancers: lip and oral cavity; nasopharynx; other pharynx; esophageal; stomach; colon and rectum; liver; gallbladder and biliary; pancreatic; larynx; tracheal, bronchus, and lung; malignant skin melanoma; nonmelanoma skin cancer; breast; cervical; uterine; ovarian; prostate; testicular; kidney; bladder; brain and nervous system; thyroid; mesothelioma; Hodgkin lymphoma; non-Hodgkin lymphoma; multiple myeloma; leukemia; and all other cancers combined. Exposure: County of residence. Main Outcomes and Measures: Age-standardized cancer mortality rates by county, year, sex, and cancer type. Results: A total of 19 511 910 cancer deaths were recorded in the United States between 1980 and 2014, including 5 656 423 due to tracheal, bronchus, and lung cancer; 2 484 476 due to colon and rectum cancer; 1 573 593 due to breast cancer; 1 077 030 due to prostate cancer; 1 157 878 due to pancreatic cancer; 209 314 due to uterine cancer; 421 628 due to kidney cancer; 487 518 due to liver cancer; 13 927 due to testicular cancer; and 829 396 due to non-Hodgkin lymphoma. Cancer mortality decreased by 20.1% (95% uncertainty interval [UI], 18.2%-21.4%) between 1980 and 2014, from 240.2 (95% UI, 235.8-244.1) to 192.0 (95% UI, 188.6-197.7) deaths per 100 000 population. There were large differences in the mortality rate among counties throughout the period: in 1980, cancer mortality ranged from 130.6 (95% UI, 114.7-146.0) per 100 000 population in Summit County, Colorado, to 386.9 (95% UI, 330.5-450.7) in North Slope Borough, Alaska, and in 2014 from 70.7 (95% UI, 63.2-79.0) in Summit County, Colorado, to 503.1 (95% UI, 464.9-545.4) in Union County, Florida. For many cancers, there were distinct clusters of counties with especially high mortality. The location of these clusters varied by type of cancer and were spread in different regions of the United States. Clusters of breast cancer were present in the southern belt and along the Mississippi River, while liver cancer was high along the Texas-Mexico border, and clusters of kidney cancer were observed in North and South Dakota and counties in West Virginia, Ohio, Indiana, Louisiana, Oklahoma, Texas, Alaska, and Illinois. Conclusions and Relevance: Cancer mortality declined overall in the United States between 1980 and 2014. Over this same period, there were important changes in trends, patterns, and differences in cancer mortality among US counties. These patterns may inform further research into improving prevention and treatment.

The burden of cancer in Mexico, 1990-2013.

OBJECTIVE: To analyze mortality and incidence for 28 cancers by deprivation status, age and sex from 1990 to 2013. MATERIALS AND METHODS: The data and methodological approaches provided by the Global Burden of Disease (GBD 2013) were used. RESULTS: Trends from 1990 to 2013 show important changes in cancer epidemiology in Mexico. While some cancers show a decreasing trend in incidence and mortality (lung, cervical) others emerge as relevant health priorities (prostate, breast, stomach, colorectal and liver cancer). Age standardized incidence and mortality rates for all cancers are higher in the northern states while the central states show a decreasing trend in the mortality rate. The analysis show that infection related cancers like cervical or liver cancer play a bigger role in more deprived states and that cancers with risk factors related to lifestyle like colorectal cancer are more common in less marginalized states. CONCLUSIONS: The burden of cancer in Mexico shows complex regional patterns by age, sex, types of cancer and deprivation status. Creation of a national cancer registry is crucial.

Effects of Doxorubicin Delivery Systems and Mild Hyperthermia on Tissue Penetration in 3D Cell Culture Models of Ovarian Cancer Residual Disease.

Current chemotherapy strategies for second-line treatment of relapsed ovarian cancer are unable to effectively treat residual disease post-cytoreduction. The findings presented herein suggest that tissue penetration of drug is not only an issue for large, unresectable tumors, but also for invisible, microscopic lesions. The present study sought to investigate the potential of a block copolymer micelle (BCM) formulation, which may reduce toxicities of doxorubicin (DOX) in a similar way to pegylated liposomal doxorubicin (PLD, Doxil/Caelyx), while enhancing penetration into tumor tissue and improving intratumoral availability of drug. To achieve this goal, 50 nm-sized BCMs capable of high DOX encapsulation (BCM-DOX) at drug levels ranging from 2 to 7.6 mg/mL were formulated using an ultrafiltration technique. BCM-DOX was evaluated in 2D and 3D cell culture of the human ovarian cancer cell lines HEYA8, OV-90, and SKOV3. Additionally, the current study examines the impact of mild hyperthermia (MHT) on the cytotoxicity of DOX. The BCM-DOX formulation fulfilled the goal of controlling drug release while providing up to 9-fold greater cell monolayer cytotoxicity in comparison to PLD. In 3D cell culture, using multicellular tumor spheroids (MCTS) as a model of residual disease postsurgery, BCM-DOX achieved the benefits of an extended release formulation of DOX and resulted in improvements in drug accumulation over PLD, while yielding drug levels approaching that achievable by exposure to DOX alone. In comparison to PLD, this translated into superior MCTS growth inhibition in the short term and comparable inhibition in the long term. Overall, although MHT appeared to enhance drug accumulation in HEYA8 MCTS treated with BCM-DOX and DOX alone in the short term, improved growth inhibition of MCTS by MHT was not observed after 48 h of drug treatment. Evaluation of BCM-DOX in comparison to PLD as well as the effects of MHT is warranted in vivo.

Expression of membrane transporters and metabolic enzymes involved in estrone-3-sulphate disposition in human breast tumour tissues.

Two-thirds of newly diagnosed hormone-dependent (HR?) breast cancers are detected in post-menopausal patients where estrone-3-sulphate (E3S) is the predominant source for tumour estradiol. Understanding intra-tumoral fate of E3S would facilitate in the identification of novel molecular targets for HR? post-menopausal breast cancer patients. Hence this study investigates the clinical expression of (i) organic anion-transporting polypeptides (OATPs), (ii) multidrug resistance protein (MRP-1), breast cancer resistance proteins (BCRP), and (iii) sulphatase (STS), 17ß-hydroxysteroid dehydrogenase (17ß-HSD-1), involved in E3S uptake, efflux and metabolism, respectively. Fluorescent and brightfield images of stained tumour sections (n = 40) were acquired at 4× and 20× magnification, respectively. Marker densities were measured as the total area of positive signal divided by the surface area of the tumour section analysed and was reported as % area (ImageJ software). Tumour, stroma and non-tumour tissue areas were also quantified (Inform software), and the ratio of optical intensity per histologic area was reported as % area/tumour, % area/stroma and % area/non-tumour. Functional role of OATPs and STS was further investigated in HR? (MCF-7, T47-D, ZR-75) and HR-(MDA-MB-231) cells by transport studies conducted in the presence or absence of specific inhibitors. Amongst all the transporters and enzymes, OATPs and STS have significantly (p < 0.0001) higher expression in HR? tumour sections with highest target signals obtained from the tumour regions of the tissues. Specific OATP-mediated E3S uptake and STS-mediated metabolism were also observed in all HR? breast cancer cells. These observations suggest the potential of OATPs as novel molecular targets for HR? breast cancers.