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Moreover, the public health and/or academic institution databases constructed with responses to different questionnaires are usually difficult to merge, impairing necessary collaborations.
Thus, these systems could potentially be used for real time monitoring of postoperative outcome in a reproducible way through existing institution databases.
This enables us to present a more accurate representation of patient survivorship than noted in previously reported smaller series of patients, which are often derived primarily from single institution databases and are often limited to patients with sarcomas of certain stage, anatomic location, and/or treatment.
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Due to the lack of published data concerning this sub-population of refractory chronic CH patients, sample size calculation was based on the estimation of characteristics of these CH patients, registered in our institution database.
Local control and breast preservation rates are obviously linked, and the supporting data for APBI include pathologic studies, historical BCT studies that show a lack of benefit elsewhere in the breast, and a growing single institution database with promising results.
The impact of conventional chemotherapy on survival appears to be minimal in the context of our retrospective cohort; perhaps these findings warrant more definitive exploration through the formation of multi-institution databases.
Therefore, single-institution databases, such as that used in this study, are still meaningful because of the consistency of treatment and pathological evaluation; the latter would result in more reliable and reproducible diagnoses of thymic malignancies.
HSDB is developing the Ontology of Clinical Research (OCRe), which defines the concepts that should be accessible across the individual institutions' databases.
Using a multi-institution database, we analyzed how practice, patient, and tumor characteristics contributed to variation in TM for invasive breast cancer.
We extended the VBCSO database to three Cancer Research Network CRNN) health plans to develop a large, non-voluntary, multi-institution database to study breast cancer surgical quality.
This prediction model was created using a single institution's database of 11,851 Korean patients and included readily available and clinically relevant factors.
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