| Title |
A case of pembrolizumab-induced type-1 diabetes mellitus and discussion of immune checkpoint inhibitor-induced type 1 diabetes
|
|---|---|
| Published in |
Cancer Immunology, Immunotherapy, October 2016
|
| DOI | 10.1007/s00262-016-1913-7 |
| Pubmed ID | |
| Authors |
Young Kwang Chae, Lauren Chiec, Nisha Mohindra, Ryan Gentzler, Jyoti Patel, Francis Giles |
| Abstract |
Immune checkpoint inhibitors such as pembrolizumab, ipilimumab, and nivolumab, now FDA-approved for use in treating several types of cancer, have been associated with immune-related adverse effects. Specifically, the antibodies targeting the programmed-cell death-1 immune checkpoint, pembrolizumab and nivolumab, have been rarely reported to induce the development of type 1 diabetes mellitus. Here we describe a case of a patient who developed antibody-positive type 1 diabetes mellitus following treatment with pembrolizumab in combination with systemic chemotherapy for metastatic adenocarcinoma of the lung. We will also provide a brief literature review of other rarely reported cases of type 1 diabetes presenting after treatment with pembrolizumab and nivolumab, as well as discussion regarding potential mechanisms of this adverse effect and its importance as these drugs continue to become even more widespread. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 85 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 13 | 15% |
| Student > Bachelor | 12 | 14% |
| Researcher | 11 | 13% |
| Student > Ph. D. Student | 11 | 13% |
| Other | 9 | 11% |
| Other | 11 | 13% |
| Unknown | 18 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 40 | 47% |
| Pharmacology, Toxicology and Pharmaceutical Science | 9 | 11% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Immunology and Microbiology | 3 | 4% |
| Nursing and Health Professions | 2 | 2% |
| Other | 4 | 5% |
| Unknown | 23 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 05 December 2016.
All research outputs
#20,359,475
of 22,908,162 outputs
Outputs from Cancer Immunology, Immunotherapy
#2,606
of 2,890 outputs
Outputs of similar age
#273,140
of 315,885 outputs
Outputs of similar age from Cancer Immunology, Immunotherapy
#29
of 33 outputs
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We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.