Significance of Tumor–Stroma Ratio (TSR) in Predicting Outcomes of Malignant Tumors
Abstract
:1. Introduction
2. Materials and Methods
2.1. Published Study Search and Selection Criteria
2.2. Data Extraction
2.3. Statistical Analyses
3. Results
3.1. Selection and Characteristics of the Studies
- A primary search using the PubMed database found 509 relevant articles. In screening and reviewing, 409 were excluded due to inapplicable or insufficient information. Among the remaining articles, 49 reports were excluded for the following reasons: non-original articles (n = 31), non-human studies (n = 5), a language other than English (n = 11), and articles including duplicated patients (n = 2) (Figure 1).
3.2. Prevalence of High Tumor–Stroma Ratio
3.3. Correlation between High Tumor–Stroma Ratio and Survival
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Author and Publication Year | Location | Organ | Criterion for High TSR | Number of Patients | Tumor–Stroma Ratio | |
---|---|---|---|---|---|---|
High | Low | |||||
Aboelnasr 2023 [39] | Egypt | Colorectum | 50% | 103 | 67 | 36 |
Alessandrini 2022 [40] | Italy | Larynx | 50% | 43 | 29 | 14 |
Almangush 2018 [8] | Finland/Brazil | Head and neck | 50% | 311 | 222 | 89 |
Aurello 2017 [9] | Italy | Stomach | 50% | 106 | 41 | 65 |
Chen 2015 [10] | China | Ovary | 50% | 838 | 575 | 263 |
Courrech Staal 2010 [11] | Netherlands | Esophagus | 50% | 93 | 60 | 33 |
de Kruijf 2011 [12] | Netherlands | Breast | 50% | 574 | 186 | 388 |
Dekker 2013 [13] | Netherlands | Breast | 50% | 403 | 241 | 162 |
Dourado 2020 [14] | Finland | Head and neck | 50% | 254 | 142 | 112 |
Geessink 2019 [15] | Netherlands | Colorectum | 50% | 129 | 87 | 42 |
Goyal 2021 [41] | India | Gallbladder | 50% | 96 | 56 | 40 |
Hansen 2018 [16] | Denmark | Colorectum | 50% | 62 | 33 | 29 |
He 2021 [42] | China | Esophagus | 50% | 270 | 113 | 157 |
Huang 2022 [43] | China | Head and neck | 50% | 151 | 84 | 67 |
Huijbers 2013 [17] | UK | Colorectum | 50% | 710 | 503 | 207 |
Huijbers 2018 [18] | UK | Colorectum | 50% | 965 | 642 | 323 |
Ichikawa 2018 [19] | Japan | Lung | 50% | 127 | 35 | 92 |
Inoue 2022 [44] | Japan | Colorectum | 85% | 200 | 100 | 100 |
Kairaluoma 2020 [20] | Finland | Liver | 50% | 47 | 34 | 13 |
Kang 2021 [45] | Korea | Colorectum | 50% | 266 | 185 | 81 |
Kang 2023 [46] | China | Head and neck | 50% | 113 | 56 | 47 |
Karpathiou 2019 [2] | France | Head and neck | 30% | 266 | 141 | 125 |
50% | 266 | 206 | 60 | |||
Kemi 2018 [21] | Sweden | Stomach | 50% | 583 | 241 | 342 |
Kim 2022 [47] | Korea | Stomach | 40% | 157 | 72 | 85 |
Labiche 2010 [22] | France | Ovary | 50% | 194 | 98 | 96 |
Li 2017 [23] | China | Gallbladder | 50% | 51 | 32 | 19 |
Li 2020 [48] | China | Pancreas | ||||
Developing cohort | 50% | 207 | 120 | 87 | ||
Validation cohort | 50% | 193 | 112 | 81 | ||
Liu 2014 [24] | China | Cervix | 50% | 184 | 147 | 37 |
Lv 2015 [25] | China | Liver | 50% | 300 | 225 | 75 |
Mascitti 2020 [26] | Italy | Head and neck | 50% | 211 | ND | ND |
Öztürk 2022 [49] | Türkiye | Breast | 50% | 105 | 104 | 101 |
Panayiotou 2015 [27] | UK | Endometrium | ND | 399 | 345 | 54 |
Peng 2018 [28] | China | Stomach | 50% | 494 | 254 | 240 |
Pongsuvareeyakul 2015 [29] | Thailand | Cervix | 50% | 131 | 93 | 38 |
Qian 2021 [50] | China | Breast | 55.5% | 240 | 93 | 147 |
Qiu 2022 [51] | China | Head and neck | 50% | 581 | 283 | 298 |
Sandberg 2018 [30] | Netherlands | Colorectum | 50% | 71 | 51 | 20 |
Scheer 2017 [31] | Netherlands | Colorectum | 30% | 154 | 118 | 36 |
70% | 154 | 48 | 106 | |||
Silva 2022 [52] | Brazil | Head and neck | 50% | 95 | NA | NA |
Smit 2020 [53] | Netherlands | Lung | 50% | 174 | 79 | 95 |
Uzun 2022 [54] | Türkiye | Gallbladder | 50% | 28 | 15 | 13 |
Vogelaar 2016 [32] | Netherlands | Colorectum | 50% | 97 | 57 | 40 |
Xi 2017 [33] | China | Lung | 50% | 261 | 223 | 38 |
Xu 2020 [34] | China | Breast | 50% | 260 | 146 | 114 |
Xu 2023 [55] | China | Urinary tract | 50% | 1015 | 622 | 393 |
Yan 2022 [56] | China | Breast | 33.5% | 240 | 153 | 87 |
Zengin 2019 [35] | Türkiye | Colorectum | 50% | 88 | 52 | 36 |
Zhang 2014 [36] | China | Head and neck | 50% | 93 | 51 | 42 |
Zhang 2015 [37] | China | Lung | 50% | 404 | 302 | 102 |
Zheng 2023 [57] | China | Urinary bladder | 45.7% | 133 | 94 | 39 |
Zong 2020 [38] | China | Cervix | 50% | 384 | 317 | 67 |
Author and Publication Year | Is the Case Definition Adequate | Representativeness of the Cases | Selection of Controls | Definition of Controls | Comparability of Cases and Controls on the Basis of the Design or Analysis | Ascertainment of Exposure | Same Method of Ascertainment for Cases and Controls | Non-Response Rate | Quality Score |
---|---|---|---|---|---|---|---|---|---|
Aboelnasr 2023 [39] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Alessandrini 2022 [40] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Almangush 2018 [8] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Aurello 2017 [9] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Chen 2015 [10] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Courrech Staal 2010 [11] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
de Kruijf 2011 [12] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Dekker 2013 [13] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Dourado 2020 [14] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Geessink 2019 [15] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Goyal 2021 [41] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Hansen 2018 [16] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
He 2021 [42] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Huang 2022 [43] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Huijbers 2013 [17] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Huijbers 2018 [18] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Ichikawa 2018 [19] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Inoue 2022 [44] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Kairaluoma 2020 [20] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Kang 2021 [45] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Kang 2023 [46] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Karpathiou 2019 [2] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Kemi 2018 [21] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Kim 2022 [47] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Labiche 2010 [22] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Li 2017 [23] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Li 2020 [48] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Liu 2014 [24] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Lv 2015 [25] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Mascitti 2020 [26] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Öztürk 2022 [49] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Panayiotou 2015 [27] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Peng 2018 [28] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Pongsuvareeyakul 2015 [29] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Qian 2021 [50] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Qiu 2022 [51] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Sandberg 2018 [30] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Scheer 2017 [31] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Silva 2022 [52] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Smit 2020 [53] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Uzun 2022 [54] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Vogelaar 2016 [32] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Xi 2017 [33] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Xu 2020 [34] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Xu 2023 [55] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Yan 2022 [56] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Zengin 2019 [35] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Zhang 2014 [36] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Zhang 2015 [37] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Zheng 2023 [57] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Zong 2020 [38] | 1 | 1 | - | 1 | 2 | 1 | 1 | 1 | 8 |
Number of Subsets | Fixed Effect (95% CI) | Heterogeneity Test (p-Value) | Random Effect (95% CI) | Egger’s Test (p-Value) | |
---|---|---|---|---|---|
Overall | 52 | 0.577 (0.588, 0.605) | <0.001 | 0.605 (0.565, 0.644) | 0.638 |
Breast | 6 | 0.483 (0.460, 0.506) | <0.001 | 0.501 (0.391, 0.612) | 0.331 |
Cervix | 3 | 0.794 (0.762, 0.823) | 0.019 | 0.785 (0.713, 0.842) | 0.375 |
Colorectum | 12 | 0.647 (0.630, 0.665) | <0.001 | 0.622 (0.556, 0.683) | 0.300 |
Endometrium | 1 | 0.865 (0.827, 0.895) | 1.000 | 0.865 (0.827, 0.895) | - |
Esophagus | 2 | 0.475 (0.423, 0.527) | <0.001 | 0.529 (0.312, 0.736) | - |
Gallbladder | 3 | 0.588 (0.514, 0.659) | 0.722 | 0.588 (0.514, 0.659) | 0.820 |
Head and neck | 8 | 0.578 (0.556, 0.600) | <0.001 | 0.594 (0.513, 0.671) | 0.393 |
Larynx | 1 | 0.674 (0.523, 0.797) | 1.000 | 0.674 (0.523, 0.797) | - |
Liver | 2 | 0.746 (0.698, 0.789) | 0.697 | 0.746 (0.698, 0.789) | - |
Lung | 4 | 0.648 (0.613, 0.680) | <0.001 | 0.606 (0.343, 0.819) | 0.544 |
Ovary | 2 | 0.650 (0.620, 0.679) | <0.001 | 0.601 (0.417, 0.761) | - |
Pancreas | 2 | 0.580 (0.531, 0.627) | 0.990 | 0.580 (0.531, 0.627) | - |
Stomach | 4 | 0.454 (0.427, 0.481) | 0.005 | 0.448 (0.387, 0.509) | 0.758 |
Urinary tract | 2 | 0.623 (0.595, 0.651) | 0.036 | 0.653 (0.556, 0.738) | - |
Criteria | |||||
<50% | 5 | 0.603 (0.570, 0.634) | <0.001 | 0.624 (0.515, 0.721) | 0.285 |
50% | 43 | 0.600 (0.591, 0.609) | <0.001 | 0.609 (0.567, 0.649) | 0.630 |
>50% | 3 | 0.408 (0.368, 0.448) | 0.001 | 0.399 (0.302, 0.506) | 0.605 |
Number of Subsets | Fixed Effect (95% CI) | Heterogeneity Test (p-Value) | Random Effect (95% CI) | Egger’s Test (p-Value) | |
---|---|---|---|---|---|
Overall | 40 | 0.657 (0.616, 0.701) | <0.001 | 0.631 (0.542, 0.734) | 0.363 |
Breast | 2 | 0.645 (0.487, 0.856) | 0.284 | 0.630 (0.443, 0.896) | - |
Cervix | 3 | 0.377 (0.258, 0.551) | 0.384 | 0.377 (0.258, 0.551) | 0.785 |
Colorectum | 10 | 0.643 (0.553, 0.747) | <0.001 | 0.588 (0.429, 0.804) | 0.308 |
Endometrium | 1 | 2.510 (1.223, 5.152) | 1.000 | 2.510 (1.223, 5.152) | - |
Esophagus | 2 | 0.406 (0.294, 0.559) | 0.854 | 0.406 (0.294, 0.559) | - |
Gallbladder | 3 | 0.574 (0.346, 0.954) | 0.132 | 0.568 (0.276, 1.169) | 0.152 |
Head and neck | 4 | 0.610 (0.496, 0.750) | 0.108 | 0.563 (0.400, 0.792) | 0.033 |
Liver | 2 | 0.503 (0.316, 0.802) | 0.140 | 0.538 (0.262, 1.105) | - |
Lung | 4 | 0.719 (0.574, 0.900) | 0.001 | 0.843 (0.482, 1.474) | 0.246 |
Ovary | 2 | 0.834 (0.711, 0.978) | 0.552 | 0.834 (0.711, 0.978) | - |
Pancreas | 2 | 1.957 (1.443, 2.654) | 0.779 | 1.957 (1.443, 2.654) | - |
Stomach | 3 | 0.498 (0.421, 0.589) | 0.063 | 0.456 (0.324, 0.641) | 0.214 |
Urinary tract | 2 | 0.599 (0.491, 0.730) | 0.048 | 0.636 (0.417, 0.971) | - |
Criteria | |||||
>50% | 3 | 0.748 (0.605, 0.924) | 0.603 | 0.748 (0.605, 0.924) | 0.388 |
50% | 34 | 0.639 (0.596, 0.684) | <0.001 | 0.593 (0.501, 0.702) | 0.206 |
>50% | 2 | 0.728 (0.483, 1.095) | 0.378 | 0.728 (0.483, 1.095) | - |
Number of Subsets | Fixed Effect (95% CI) | Heterogeneity Test (p-Value) | Random Effect (95% CI) | Egger’s Test (p-Value) | |
---|---|---|---|---|---|
Overall | 29 | 0.571 (0.522, 0.623) | <0.001 | 0.564 (0.476, 0.669) | 0.551 |
Breast | 4 | 0.517 (0.423, 0.632) | 0.313 | 0.517 (0.415, 0.645) | 0.848 |
Cervix | 3 | 0.447 (0.307, 0.650) | 0.519 | 0.447 (0.307, 0.650) | 0.351 |
Colorectum | 6 | 0.609 (0.518, 0.716) | 0.200 | 0.609 (0.490, 0.759) | 0.826 |
Endometrium | 1 | 2.180 (1.146, 4.146) | 1.000 | 2.180 (1.146, 4.146) | - |
Esophagus | 1 | 0.458 (0.281, 0.746) | 1.000 | 0.458 (0.281, 0.746) | - |
Head and neck | 8 | 0.592 (0.495, 0.710) | <0.001 | 0.661 (0.430, 1.017) | 0.366 |
Larynx | 1 | 0.089 (0.025, 0.323) | 1.000 | 0.089 (0.025, 0.323) | - |
Lung | 3 | 0.628 (0.497, 0.794) | 0.519 | 0.628 (0.497, 0.794) | 0.725 |
Stomach | 2 | 0.181 (0.090, 0.364) | 0.239 | 0.176 (0.077, 0.405) | - |
Criteria | |||||
<50% | 3 | 0.475 (0.348, 0.648) | 0.009 | 0.466 (0.222, 0.981) | 0.959 |
50% | 23 | 0.560 (0.509, 0.617) | <0.001 | 0.545 (0.457, 0.650) | 0.320 |
>50% | 2 | 0.618 (0.430, 0.889) | 0.801 | 0.618 (0.430, 0.889) | - |
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Pyo, J.-S.; Kim, N.Y.; Min, K.-W.; Kang, D.-W. Significance of Tumor–Stroma Ratio (TSR) in Predicting Outcomes of Malignant Tumors. Medicina 2023, 59, 1258. https://doi.org/10.3390/medicina59071258
Pyo J-S, Kim NY, Min K-W, Kang D-W. Significance of Tumor–Stroma Ratio (TSR) in Predicting Outcomes of Malignant Tumors. Medicina. 2023; 59(7):1258. https://doi.org/10.3390/medicina59071258
Chicago/Turabian StylePyo, Jung-Soo, Nae Yu Kim, Kyueng-Whan Min, and Dong-Wook Kang. 2023. "Significance of Tumor–Stroma Ratio (TSR) in Predicting Outcomes of Malignant Tumors" Medicina 59, no. 7: 1258. https://doi.org/10.3390/medicina59071258