Evidence map›Paper›PMID 31539415›Full record

ArticlePloS one2019

Potential survival benefits from optimized chemotherapy implementation in advanced ovarian cancer: Projections from a microsimulation model.

Anna P Lietz, Davis T Weaver, Alexander Melamed, Jose Alejandro Rauh-Hain, Jason D Wright, Alexi A Wright, Amy B Knudsen, Pari V Pandharipande

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 86% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Anna P LietzInstitute for Technology Assessment, Massachusetts General Hospital, Boston, MA, United States of America.
Davis T WeaverInstitute for Technology Assessment, Massachusetts General Hospital, Boston, MA, United States of America.
Alexander MelamedDivision of Gynecologic Oncology, Vincent Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, United States of America.
Jose Alejandro Rauh-HainGynecologic Oncology and Reproductive Medicine Department, University of Texas MD Anderson Cancer Center, Houston TX, United States of America.
Jason D WrightDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology, Columbia University College of Physicians and Surgeons, New York, NY, United States of America.
Alexi A WrightDana-Farber Cancer Institute, Boston, MA, United States of America.
Amy B KnudsenInstitute for Technology Assessment, Massachusetts General Hospital, Boston, MA, United States of America.
Pari V PandharipandeInstitute for Technology Assessment, Massachusetts General Hospital, Boston, MA, United States of America.
Massachusetts General Hospital · USColumbia University · USDana-Farber Cancer Institute · USThe University of Texas MD Anderson Cancer Center · US

Funding

Obstetrical and Oncological Outcomes Among Reproductive Age Women with Gynecological and Breast CancerK08CA234333 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI RAUH-HAIN, JOSE ALEJANDRO · 2018 to 2022
$1.2M
NCI NIH HHS K08 CA234333
6 · The paper itself

Abstract

backgroundOvarian cancer is often diagnosed in advanced stages, when survival is poor. Treatment advances have been made, but are inconsistently implemented. Our purpose was to project the maximum life expectancy gains that could be achieved in women with stage IIIC epithelial ovarian cancer if the implementation of available chemotherapy regimens could be optimized.

methodsWe used a microsimulation model to estimate life expectancy benefits associated with "optimized" implementation of four post-operative chemotherapy options: standard intravenous chemotherapy; intraperitoneal + intravenous chemotherapy; bevacizumab + intravenous chemotherapy; and hyperthermic intraperitoneal chemotherapy + intravenous chemotherapy. Optimized implementation was defined as follows. Patients triaged to primary cytoreductive surgery received intraperitoneal + intravenous chemotherapy if optimally or completely cytoreduced, and bevacizumab + intravenous chemotherapy if suboptimally cytoreduced. Patients triaged to neoadjuvant chemotherapy received hyperthermic intraperitoneal chemotherapy at interval cytoreductive surgery if optimally or completely cytoreduced, and standard IV chemotherapy if suboptimally cytoreduced. Life expectancy associated with optimized implementation was compared with that of current utilization practices, estimated using published literature and the National Cancer Database. Effects of model uncertainty were evaluated in sensitivity analyses.

resultsLife expectancy associated with optimized implementation vs. current practice was 76.7 vs. 64.5 months (life expectancy gain = 12.2 months). Providing intraperitoneal + intravenous chemotherapy to all eligible patients was the largest driver of life expectancy gains, due to both the potential benefit conferred by intraperitoneal + intravenous chemotherapy and the proportion of eligible women who do not receive intraperitoneal + intravenous chemotherapy in current practice.

conclusionPopulation-level life expectancy in stage IIIC epithelial ovarian cancer could be substantially improved through greater uptake of available chemotherapy regimens.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsBevacizumabCombined Modality TherapyCytoreduction Surgical ProceduresDisease-Free SurvivalDrug TherapyFemaleHumansKaplan-Meier EstimateMiddle AgedOvarian NeoplasmsBevacizumab

Identifiers

PMID31539415
PMCPMC6754166
OpenAlexW2973615613

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.