To describe treatment patterns, outcomes and healthcare resource use in patients with metastatic and/or locally recurrent, unresectable gastric cancer (MGC) in Taiwan.
Patients who had received first-line therapy (platinum and/or fluoropyrimidine) followed by second-line therapy or best supportive care (BSC) only were eligible. Participating physicians provided de-identified information from patient charts. Data were summarized descriptively and Kaplan-Meier analysis was used to describe time to events.
Overall, 37 physicians contributed 122 patient charts. Of the 122 patients (median age, 61 years; 62% male), 43 (35%) received BSC only following first-line therapy, whereas 79 (65%) received second-line therapy. There was heterogeneity in second-line treatment, although fluoropyrimidine with or without a platinum agent was most frequently used. Median survival was 12.5 (interquartile range [IQR], 8.2-20.8) months from MGC diagnosis for patients receiving second-line therapy and 8.0 (IQR, 5.6-not reached) months for patients receiving BSC only. The most common treatment-related symptoms were nausea/vomiting (58%); the most common cancer-related symptoms were pain (61%), ascites (35%) and nausea/vomiting (33%). Inpatient and outpatient hospitalizations were numerically more common for patients receiving second-line therapy than for those receiving BSC only; the prevalence of hospice and skilled nursing facility stays were numerically more common for patients receiving BSC only.
In this Taiwanese MGC population, 65% received active second-line therapy with heterogeneity seen in the regimen used. Clinical outcomes suggest an unmet medical need in this population. This study may help inform clinical practice and future research to ultimately improve patient outcomes in Taiwan.
© 2016 John Wiley & Sons Australia, Ltd.

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AP32788 is a tyrosine kinase inhibitor (TKI) designed to address an unmet medical need in a subset of non-small cell lung cancers (Company Pipeline, Ariad, APR 26, 2016, View Source [SID:1234511400]). Using our targeted structure-based drug discovery methods, ARIAD’s research team worked to design and build this molecule and see it from concept to nomination in under a year –a testament to the process, science, and people involved in ARIAD’s drug discovery group.

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In December 2014, we nominated AP32788 for clinical development and are currently conducting studies necessary to support the filing of an investigational new drug (IND) application. We expect to file the IND by the end of 2015 and to commence a Phase 1/2 proof-of-concept clinical trial of AP32788 in 2016.

We had previously developed an algorithm for Medicare claims data to detect bone metastases associated with breast, prostate, or lung cancer. This study was conducted to examine whether this algorithm accurately documents bone metastases on the basis of diagnosis codes in Medicare claims data.
We obtained data from Medicare claims and electronic medical records of patients 65 years or older with a breast, prostate, or lung cancer diagnosis at a teaching hospital and/or affiliated clinics during 2005 or 2006. We calculated the sensitivity and positive predictive value (PPV) of our algorithm using medical records as the "gold standard." The κ statistic was used to measure agreement between claims and medical record data.
The agreement between claims and medical record data for bone metastases among breast, prostate, and lung cancer patients was 0.93, 0.90, and 0.69, respectively. The sensitivities of our algorithm for bone metastasis in patients with breast, prostate, and lung were 96.8% [95% confidence interval (CI)=83.8% to 99.4%], 91.7% (95% CI=78.2% to 97.1%), and 74.1% (95% CI=55.3% to 86.8%), respectively; and the PPVs were 90.9% (95% CI=76.4% to 96.9%), 91.7% (95% CI=78.2% to 97.1%), and 71.4% (95% CI=52.9% to 84.8%), respectively.
The algorithm for detecting bone metastases in claims data had high sensitivity and PPV for breast and prostate cancer patients. Sensitivity and PPV were lower but still moderate for lung cancer patients.

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To prospectively test the diagnostic accuracy of the percentage of prostate specific antigen (PSA) isoform [-2]proPSA (%p2PSA) and the Prostate Health Index (PHI), and to determine their role for discrimination between significant and insignificant prostate cancer at initial and repeat prostate biopsy in men aged ≤65 years.
The diagnostic performance of %p2PSA and PHI were evaluated in a multicentre study. In all, 769 men aged ≤65 years scheduled for initial or repeat prostate biopsy were recruited in four sites based on a total PSA (t-PSA) level of 1.6-8.0 ng/mL World Health Organization (WHO) calibrated (2-10 ng/mL Hybritech-calibrated). Serum samples were measured for the concentration of t-PSA, free PSA (f-PSA) and p2PSA with Beckman Coulter immunoassays on Access-2 or DxI800 instruments. PHI was calculated as (p2PSA/f-PSA × √t-PSA). Uni- and multivariable logistic regression models and an artificial neural network (ANN) were complemented by decision curve analysis (DCA).
In univariate analysis %p2PSA and PHI were the best predictors of prostate cancer detection in all patients (area under the curve [AUC] 0.72 and 0.73, respectively), at initial (AUC 0.67 and 0.69) and repeat biopsy (AUC 0.74 and 0.74). t-PSA and %f-PSA performed less accurately for all patients (AUC 0.54 and 0.62). For detection of significant prostate cancer (based on Prostate Cancer Research International Active Surveillance [PRIAS] criteria) the %p2PSA and PHI equally demonstrated best performance (AUC 0.70 and 0.73) compared with t-PSA and %f-PSA (AUC 0.54 and 0.59). In multivariate analysis PHI we added to a base model of age, prostate volume, digital rectal examination, t-PSA and %f-PSA. PHI was strongest in predicting prostate cancer in all patients, at initial and repeat biopsy and for significant prostate cancer (AUC 0.73, 0.68, 0.78 and 0.72, respectively). In DCA for all patients the ANN showed the broadest threshold probability and best net benefit. PHI as single parameter and the base model + PHI were equivalent with threshold probability and net benefit nearing those of the ANN. For significant cancers the ANN was the strongest parameter in DCA.
The present multicentre study showed that %p2PSA and PHI have a superior diagnostic performance for detecting prostate cancer in the PSA range of 1.6-8.0 ng/mL compared with t-PSA and %f-PSA at initial and repeat biopsy and for predicting significant prostate cancer in men aged ≤65 years. They are equally superior for counselling patients before biopsy.
© 2015 The Authors BJU International © 2015 BJU International Published by John Wiley & Sons Ltd.

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The treatment of autoimmune disorders has been revolutionised by the introduction of biologics such as anti-tumour necrosis factor (anti-TNF). Although in rheumatoid arthritis patients a bone sparing effect of anti-TNF has been shown, the mechanism is not fully understood. Anti-TNF molecules block tumour necrosis factor (TNF) and prevent signalling via both TNF receptor 1 (TNFR1; p55) and TNF receptor 2 (TNFR2; p75). However, signalling via TNFR2 is reported to have protective effects in a number of cell and organ systems. Hence we set out to investigate if pharmacological inhibition of TNFR1 had differential effects compared to pan-TNF inhibition in both an in vitro cell-based model of human osteoclast activity and an in vivo mouse model of lipopolysaccharide (LPS)-induced osteolysis. For the in vitro experiments the anti-human TNFR1 domain antibody (dAb) DMS5541 was used, whereas for the in vivo mouse experiments the anti-mouse TNFR1 dAb DMS5540 was used. We show that selective blocking of TNFR1 signalling reduced osteoclast formation in the presence of TNF. Subcutaneous LPS injection over the calvaria leads to the development of osteolytic lesions within days due to inflammation driven osteoclast formation. In this model, murine TNFR2 genetically fused with mouse IgG1 Fc domain (mTNFR2.Fc), an anti-TNF, did not protect from bone loss in contrast to anti-TNFR1, which significantly reduced lesion development, inflammatory infiltrate, and osteoclast number and size. These results support further exploring the use of TNFR1-selective inhibition in inflammatory bone loss disorders such as osteomyelitis and peri-prosthetic aseptic loosening.
Copyright © 2015 Elsevier Inc. All rights reserved.

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