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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Validation of Claims Algorithms for Progression to Metastatic Cancer in Patients with Breast, Non-small Cell Lung, and Colorectal Cancer
|
|---|---|
| Published in |
Frontiers in oncology, February 2016
|
| DOI | 10.3389/fonc.2016.00018 |
| Pubmed ID | |
| Authors |
Beth L. Nordstrom, Jason C. Simeone, Karen G. Malley, Kathy H. Fraeman, Zandra Klippel, Mark Durst, John H. Page, Hairong Xu |
| Abstract |
Validated algorithms for identifying progression to metastatic cancer could permit the use of administrative claims databases for research in this area. To identify simple algorithms that could accurately detect cancer progression to metastatic breast, non-small cell lung, and colorectal cancer (CRC) using medical and pharmacy claims data. Adults with stage I-III breast, non-small cell lung cancer (NSCLC), or CRC in the Geisinger Health System from 2004 to 2011 were selected. Evidence of progression was extracted via manual chart review as the reference standard. In addition to secondary malignancy diagnosis (ICD-9 code for metastases), diagnoses, procedures, and treatments were selected with clinician input as indicators of cancer progression. Random forests models provided variable importance scores. In addition to codes for secondary malignancy, several more complex algorithms were constructed and performance measures calculated. Among those with breast cancer [17/502 (3.4%) progressed], the performance of a secondary malignancy code was suboptimal [sensitivity: 64.7%; specificity: 86.0%; positive predictive value (PPV): 13.9; negative predictive value (NPV): 98.6%]; requiring malignancy at another site or initiation of immunotherapy increased PPV and specificity but decreased sensitivity. For NSCLC [61/236 (25.8%) progressed], codes for secondary malignancy alone (PPV: 47.4%; NPV: 84.8%; sensitivity: 60.7%; specificity: 76.6%) performed similarly or better than more complex algorithms. For CRC [33/276 (12.0%) progressed], secondary malignancy codes had good specificity (92.7%) and NPV (92.3%) but low sensitivity (42.4%) and PPV (43.8%); an algorithm with change in chemotherapy increased sensitivity but decreased other metrics. Selected algorithms performed similarly to the presence of a secondary tumor diagnosis code, with low sensitivity/PPV and higher specificity/NPV. Accurate identification of cancer progression likely requires verification through chart review. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 13% |
| Student > Master | 5 | 11% |
| Student > Doctoral Student | 4 | 9% |
| Other | 4 | 9% |
| Researcher | 4 | 9% |
| Other | 8 | 17% |
| Unknown | 15 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 39% |
| Engineering | 3 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
| Social Sciences | 2 | 4% |
| Nursing and Health Professions | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 16 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 December 2019.
All research outputs
#3,274,687
of 25,374,647 outputs
Outputs from Frontiers in oncology
#922
of 22,416 outputs
Outputs of similar age
#54,633
of 406,424 outputs
Outputs of similar age from Frontiers in oncology
#9
of 86 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,416 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 406,424 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.