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PubMed Multi-Term Publication Trend Comparator
x402
PubMed Multi-Term Publication Trend Comparator is a paid API for AI agents from pubmed.sekgen.xyz, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-13).
Compares biomedical publication trends across multiple PubMed search terms side-by-side, with growth rates, CAGR rankings, and crossover detection
Price / call$0.02
Success—
StatusUnknown
How this service works
Compare biomedical publication trends across multiple PubMed search terms — side-by-side growth, CAGR ranking, and crossover detection for medical and scientific research
Output
Returns a side-by-side comparison of publication counts and growth metrics for multiple PubMed search terms, including year-by-year trend data, compound annual growth rates (CAGR) ranked across all terms, and detected crossover points where one topic's publication volume surpassed another.
Example use cases
Track emerging vs established cancer treatments
“Show me how PubMed publication trends compare across 'traditional chemotherapy', 'targeted therapy', and 'immunotherapy' over the last decade. I need to see which treatment approaches are getting the most research attention and if any of them have overtaken each other in publication volume.”
Monitor vaccine research momentum shifts
“Can you compare the publication growth for 'mRNA vaccines', 'viral vector vaccines', and 'protein subunit vaccines' on PubMed? I want to see their year-by-year counts, rank them by growth rate, and identify when mRNA research started dominating the field.”
Benchmark competing diagnostic technologies
“Pull the PubMed publication trends for 'liquid biopsy', 'circulating tumor DNA', and 'digital pathology' side by side. Show me which diagnostic approach has accelerating research output, how their growth rates compare, and if any have crossed over in publication volume recently.”
Technical details
Endpoint
GEThttps://pubmed.sekgen.xyz/api/v1/compareWhen to prefer
Use this endpoint when you need to compare the relative research momentum of two or more biomedical topics simultaneously — especially when you want ranked CAGR, crossover detection, or side-by-side trend lines rather than a single topic's standalone growth curve.
Side effects
- Invalid or empty search terms return no results
- Too many simultaneous terms may exceed query limits
- PubMed API unavailability causes upstream failures
- Ambiguous search terms may return noisy or unexpected counts
- Payment failure (x402) prevents access to results
Input
{
"input": {
"type": "http",
"method": "GET",
"queryParams": {
"terms": "immunotherapy,gene therapy",
"end_year": "2023",
"start_year": "2015"
}
}
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
{
"terms": [
"immunotherapy",
"gene therapy"
],
"series": {
"gene therapy": {
"cagr": 0.010007014608022224,
"data": [
{
"year": 2015,
"count": 28414,
"proportion": 0.022583252595595734,
"yoy_growth": null,
"total_pubmed": 1258189
},
{
"year": 2016,
"count": 28834,
"proportion": 0.022429903634027113,
"yoy_growth": 0.014781445766171606,
"total_pubmed": 1285516
},
{
"year": 2017,
"count": 29791,
"proportion": 0.022839185790041405,
"yoy_growth": 0.03318998404661164,
"total_pubmed": 1304381
},
{
"year": 2018,
"count": 30548,
"proportion": 0.02260004039420602,
"yoy_growth": 0.02541035883320466,
"total_pubmed": 1351679
},
{
"year": 2019,
"count": 31975,
"proportion": 0.022533744237950702,
"yoy_growth": 0.04671336912400157,
"total_pubmed": 1418983
},
{
"year": 2020,
"count": 35188,
"proportion": 0.02143963871637566,
"yoy_growth": 0.10048475371383894,
"total_pubmed": 1641259
},
{
"year": 2021,
"count": 36729,
"proportion": 0.020547577356210593,
"yoy_growth": 0.04379333863817211,
"total_pubmed": 1787510
},
{
"year": 2022,
"count": 31725,
"proportion": 0.017788715478116935,
"yoy_growth": -0.13624111737319283,
"total_pubmed": 1783434
},
{
"year": 2023,
"count": 30770,
"proportion": 0.018121553989509875,
"yoy_growth": -0.030102442868400314,
"total_pubmed": 1697978
}
],
"trend_direction": "declining"
},
"immunotherapy": {
"cagr": 0.12159321717062999,
"data": [
{
"year": 2015,
"count": 13199,
"proportion": 0.010490474801480541,
"yoy_growth": null,
"total_pubmed": 1258189
},
{
"year": 2016,
"count": 14388,
"proportion": 0.011192392782353545,
"yoy_growth": 0.09008258201378892,
"total_pubmed": 1285516
},
{
"year": 2017,
"count": 16110,
"proportion": 0.012350685880889096,
"yoy_growth": 0.11968306922435362,
"total_pubmed": 1304381
},
{
"year": 2018,
"count": 18149,
"proportion": 0.01342700448849172,
"yoy_growth": 0.1265673494723774,
"total_pubmed": 1351679
},
{
"year": 2019,
"count": 20358,
"proportion": 0.01434689492404067,
"yoy_growth": 0.12171469502451926,
"total_pubmed": 1418983
},
{
"year": 2020,
"count": 25369,
"proportion": 0.015457036336129763,
"yoy_growth": 0.24614402200609098,
"total_pubmed": 1641259
},
{
"year": 2021,
"count": 32879,
"proportion": 0.018393743251786002,
"yoy_growth": 0.29603058851354014,
"total_pubmed": 1787510
},
{
"year": 2022,
"count": 35762,
"proportion": 0.02005232601823224,
"yoy_growth": 0.08768514857507832,
"total_pubmed": 1783434
},
{
"year": 2023,
"count": 33054,
"proportion": 0.019466683313918084,
"yoy_growth": -0.07572283429338404,
"total_pubmed": 1697978
}
],
"trend_direction": "stable"
}
},
"source": "pubmed",
"end_year": 2023,
"start_year": 2015,
"crossover_years": {
"immunotherapy > gene therapy": 2022
},
"ranking_by_growth": [
"immunotherapy",
"gene therapy"
]
}Tags
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