Future directions in the evaluation and management of newly diagnosed metastatic cancer

Eric J. Lehrer; Chachrit Khunsriraksakul; Sara Garrett; Daniel M. Trifiletti; Jason P. Sheehan; Matthias Guckenberger; Alexander V. Louie; Shankar Siva; Piet Ost; Karyn A. Goodman; Laura A. Dawson; Leila T. Tchelebi; Jonathan T. Yang; Timothy N. Showalter; Henry S. Park; Daniel E. Spratt; Amar U. Kishan; Gaorav P. Gupta; Chirag Shah; Stefano Fanti; Jeremie Calais; Ming Wang; Kathryn Schmitz; Dajiang Liu; John A. Abraham; Robert T. Dess; Irène Buvat; Benjamin Solomon; Nicholas G. Zaorsky

doi:10.1016/j.critrevonc.2025.104631

Future directions in the evaluation and management of newly diagnosed metastatic cancer

Eric J. Lehrer, Chachrit Khunsriraksakul, Sara Garrett, Daniel M. Trifiletti, Jason P. Sheehan, Matthias Guckenberger, Alexander V. Louie, Shankar Siva, Piet Ost, Karyn A. Goodman, Laura A. Dawson, Leila T. Tchelebi, Jonathan T. Yang, Timothy N. Showalter, Henry S. Park, Daniel E. Spratt, Amar U. Kishan, Gaorav P. Gupta, Chirag Shah, Stefano FantiJeremie Calais, Ming Wang, Kathryn Schmitz, Dajiang Liu, John A. Abraham, Robert T. Dess, Irène Buvat, Benjamin Solomon, Nicholas G. Zaorsky

Research output: Contribution to journal › Review article › peer-review

Abstract

There is much debate regarding optimal selection in patients with metastatic cancer who should undergo local treatment (surgery or radiation treatment) to the primary tumor and/or metastases. Additionally, the optimal treatment of newly diagnosed metastatic cancer is largely unclear. Current prognostication systems to best inform these clinical scenarios are limited, as all metastatic patients are grouped together as having Stage IV disease without further incorporation of patient and disease-specific covariates that significantly impact patient outcomes. Therefore, improving current prognostic scoring systems and incorporation of these covariates is essential to best individualize treatment for patients with metastatic cancer. In this narrative review article, we provide a detailed review of prognostication systems that can be used for both the site of metastasis and primary site to best tailor treatment in these patients. Additionally, we discuss the incorporation and ongoing developments in radiographic, genomic, and biostatistical techniques that can be used as prognostication tools.

Original language	English (US)
Article number	104631
Journal	Critical Reviews in Oncology/Hematology
Volume	208
DOIs	https://doi.org/10.1016/j.critrevonc.2025.104631
State	Published - Apr 2025

All Science Journal Classification (ASJC) codes

Hematology
Oncology
Geriatrics and Gerontology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.critrevonc.2025.104631

Cite this

Lehrer, E. J., Khunsriraksakul, C., Garrett, S., Trifiletti, D. M., Sheehan, J. P., Guckenberger, M., Louie, A. V., Siva, S., Ost, P., Goodman, K. A., Dawson, L. A., Tchelebi, L. T., Yang, J. T., Showalter, T. N., Park, H. S., Spratt, D. E., Kishan, A. U., Gupta, G. P., Shah, C., ... Zaorsky, N. G. (2025). Future directions in the evaluation and management of newly diagnosed metastatic cancer. Critical Reviews in Oncology/Hematology, 208, Article 104631. https://doi.org/10.1016/j.critrevonc.2025.104631

@article{ec9da8997c1f42c29fb75ef4d1e26cd3,

title = "Future directions in the evaluation and management of newly diagnosed metastatic cancer",

abstract = "There is much debate regarding optimal selection in patients with metastatic cancer who should undergo local treatment (surgery or radiation treatment) to the primary tumor and/or metastases. Additionally, the optimal treatment of newly diagnosed metastatic cancer is largely unclear. Current prognostication systems to best inform these clinical scenarios are limited, as all metastatic patients are grouped together as having Stage IV disease without further incorporation of patient and disease-specific covariates that significantly impact patient outcomes. Therefore, improving current prognostic scoring systems and incorporation of these covariates is essential to best individualize treatment for patients with metastatic cancer. In this narrative review article, we provide a detailed review of prognostication systems that can be used for both the site of metastasis and primary site to best tailor treatment in these patients. Additionally, we discuss the incorporation and ongoing developments in radiographic, genomic, and biostatistical techniques that can be used as prognostication tools.",

author = "Lehrer, {Eric J.} and Chachrit Khunsriraksakul and Sara Garrett and Trifiletti, {Daniel M.} and Sheehan, {Jason P.} and Matthias Guckenberger and Louie, {Alexander V.} and Shankar Siva and Piet Ost and Goodman, {Karyn A.} and Dawson, {Laura A.} and Tchelebi, {Leila T.} and Yang, {Jonathan T.} and Showalter, {Timothy N.} and Park, {Henry S.} and Spratt, {Daniel E.} and Kishan, {Amar U.} and Gupta, {Gaorav P.} and Chirag Shah and Stefano Fanti and Jeremie Calais and Ming Wang and Kathryn Schmitz and Dajiang Liu and Abraham, {John A.} and Dess, {Robert T.} and Ir{\`e}ne Buvat and Benjamin Solomon and Zaorsky, {Nicholas G.}",

note = "Publisher Copyright: {\textcopyright} 2025 Elsevier B.V.",

year = "2025",

month = apr,

doi = "10.1016/j.critrevonc.2025.104631",

language = "English (US)",

volume = "208",

journal = "Critical Reviews in Oncology/Hematology",

issn = "1040-8428",

publisher = "Elsevier Ireland Ltd",

}

Lehrer, EJ, Khunsriraksakul, C, Garrett, S, Trifiletti, DM, Sheehan, JP, Guckenberger, M, Louie, AV, Siva, S, Ost, P, Goodman, KA, Dawson, LA, Tchelebi, LT, Yang, JT, Showalter, TN, Park, HS, Spratt, DE, Kishan, AU, Gupta, GP, Shah, C, Fanti, S, Calais, J, Wang, M, Schmitz, K, Liu, D, Abraham, JA, Dess, RT, Buvat, I, Solomon, B & Zaorsky, NG 2025, 'Future directions in the evaluation and management of newly diagnosed metastatic cancer', Critical Reviews in Oncology/Hematology, vol. 208, 104631. https://doi.org/10.1016/j.critrevonc.2025.104631

TY - JOUR

T1 - Future directions in the evaluation and management of newly diagnosed metastatic cancer

AU - Lehrer, Eric J.

AU - Khunsriraksakul, Chachrit

AU - Garrett, Sara

AU - Trifiletti, Daniel M.

AU - Sheehan, Jason P.

AU - Guckenberger, Matthias

AU - Louie, Alexander V.

AU - Siva, Shankar

AU - Ost, Piet

AU - Goodman, Karyn A.

AU - Dawson, Laura A.

AU - Tchelebi, Leila T.

AU - Yang, Jonathan T.

AU - Showalter, Timothy N.

AU - Park, Henry S.

AU - Spratt, Daniel E.

AU - Kishan, Amar U.

AU - Gupta, Gaorav P.

AU - Shah, Chirag

AU - Fanti, Stefano

AU - Calais, Jeremie

AU - Wang, Ming

AU - Schmitz, Kathryn

AU - Liu, Dajiang

AU - Abraham, John A.

AU - Dess, Robert T.

AU - Buvat, Irène

AU - Solomon, Benjamin

AU - Zaorsky, Nicholas G.

PY - 2025/4

Y1 - 2025/4

N2 - There is much debate regarding optimal selection in patients with metastatic cancer who should undergo local treatment (surgery or radiation treatment) to the primary tumor and/or metastases. Additionally, the optimal treatment of newly diagnosed metastatic cancer is largely unclear. Current prognostication systems to best inform these clinical scenarios are limited, as all metastatic patients are grouped together as having Stage IV disease without further incorporation of patient and disease-specific covariates that significantly impact patient outcomes. Therefore, improving current prognostic scoring systems and incorporation of these covariates is essential to best individualize treatment for patients with metastatic cancer. In this narrative review article, we provide a detailed review of prognostication systems that can be used for both the site of metastasis and primary site to best tailor treatment in these patients. Additionally, we discuss the incorporation and ongoing developments in radiographic, genomic, and biostatistical techniques that can be used as prognostication tools.

AB - There is much debate regarding optimal selection in patients with metastatic cancer who should undergo local treatment (surgery or radiation treatment) to the primary tumor and/or metastases. Additionally, the optimal treatment of newly diagnosed metastatic cancer is largely unclear. Current prognostication systems to best inform these clinical scenarios are limited, as all metastatic patients are grouped together as having Stage IV disease without further incorporation of patient and disease-specific covariates that significantly impact patient outcomes. Therefore, improving current prognostic scoring systems and incorporation of these covariates is essential to best individualize treatment for patients with metastatic cancer. In this narrative review article, we provide a detailed review of prognostication systems that can be used for both the site of metastasis and primary site to best tailor treatment in these patients. Additionally, we discuss the incorporation and ongoing developments in radiographic, genomic, and biostatistical techniques that can be used as prognostication tools.

UR - http://www.scopus.com/inward/record.url?scp=85217398468&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85217398468&partnerID=8YFLogxK

U2 - 10.1016/j.critrevonc.2025.104631

DO - 10.1016/j.critrevonc.2025.104631

M3 - Review article

C2 - 39864534

AN - SCOPUS:85217398468

SN - 1040-8428

VL - 208

JO - Critical Reviews in Oncology/Hematology

JF - Critical Reviews in Oncology/Hematology

M1 - 104631

ER -

Future directions in the evaluation and management of newly diagnosed metastatic cancer

Abstract

All Science Journal Classification (ASJC) codes

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this