Introduction
Methods
Protocol and registration
Eligibility criteria
Search strategy
Study selection
Data extraction and analysis
Results
Study characteristics
Author, Year, Country, Study Design | Cancer Type | N | Mean Age in Years (SD) | Frailty Index Name | FI Categories | FI Items | Mean FI (SD) | Frailty Prevalence | Rationale and Comments |
---|---|---|---|---|---|---|---|---|---|
Giri 2021 USA [25] Observational | Gastrointestinal | 455 | Median 68 (IQR 64–74) | CARE Frailty Index | > 0.35 (frail) 0.2—0.35 (prefrail) < 0.2 (robust) | 44 | NR | 36.8% frail 30% prefrail 33.2% robust | Referenced Searle et al. [27] which did not categorise FI |
Giri 2022 USA [26] Observational | Various | 603 | Median 69 (IQR 64–74) | CARE Frailty Index | > 0.35 (frail) 0.2—0.35 (prefrail) < 0.2 (robust) | 44 | NR | 36.2% frail 29.0% pre-frail 33.2% robust | Referenced Searle et al. [27] which did not categorise FI |
Williams 2022 USA [39] Observational | Gastrointestinal | 553 | 69.9 (7.1) | CARE Frailty Index | > 0.35 (frail) 0.20—0.35 (pre-frail) 0—0.20 (robust) | 44 | White median 0.3 (range 0.0–0.9) Black median 0.4 (range 0.0–0.8) | 36.7% frail | Referenced Searle et al. [27] which did not categorise FI |
Guerard 2017 USA [27] Observational | Various including haematological | 546 | Median 72 (range 65–100) | Carolina Frailty Index (CFI) | > 0.35 (frail) 0.2—0.35 (pre-frail) 0—0.2 (robust) | 36 | NR | 18% frail 24% pre-frail 58% robust | Nil |
Nishijima 2017 USA [33] Observational | Various | 133 | Median 74 (range 65–92) | Carolina Frailty Index (CFI) | ≥ 0.35 (frail) 0.20 ≤ FI < 0.35 (pre-frail) < 0.20 (robust) | 36 | 0.22 (0.16) | 24% frail 22% prefrail 54% robust | Referenced study by co-authors Guerard et al. [25] |
Williams 2018 USA [37] Observational | Various including haematological | 162 | Median 71 (IQR 68–77) | Carolina Frailty Index (CFI) | > 0.35 (frail) 0.20—0.35 (pre-frail) < 0.20 (robust) | 36 | NR | 21% frail 27% pre-frail 53% robust | Indirectly referenced work by co-authors Guerard et al. [18] |
Williams 2019 USA [38] Observational | Breast | 63 | 70 (range 65–86) | Carolina Frailty Index (CFI) | > 0.35 (frail) 0.20—0.35 (pre-frail) < 0.20 (robust) | 36 | NR | 5% frail 18% pre-frail 78% robust | |
Zhou 2021 USA [58] Observational | Breast | 46,027 | Median 74 (NR) | Claims-based Frailty Index | ≥ 0.35 (frail) 0.20—0.35 (pre-frail) ≤ 0.20 (fit) | 93 | NR | 7.1% frail 36.7% pre-frail 66.6% fit | Referenced validation paper for claims-based frailty index [ref] and Cohen et al.[ref] |
Ahles 2021 USA [19] Observational | Breast | 490ꝉ including 162 non-cancer controls | 72.6 (6.0) | Deficit Accumulation Frailty Index (DAFI) | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.2 (robust/nonfrail) | 44 | NR | 7% frail 24% prefrail 69% robust 7% missing | Referenced a study by a co-author, Cohen et al. [22] |
Ahles 2022 USA [20] Observational | Breast | 490a including 162 non-cancer controls | 72.6 (6.0) | Deficit Accumulation Frailty Index (DAFI) | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.2 (robust/nonfrail) | 44 | NR | 7% frail 24% prefrail 69% robust 7% missing | |
Gilmore 2021 USA [23] Secondary analysis of RCT | Various including lymphoma | 541c | 76.6 (5.22) | Deficit Accumulation Index (DAI) | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.2 (robust) | 48 | NR | 32.5% frail 40.9% prefrail 26.4% robust | Referenced a study by a co-author, Cohen et al. [22] |
Gilmore 2022 USA [24] Secondary analysis of RCT | Various including lymphoma | 541c | 76.6 (range 70–96) | Deficit Accumulation Index (DAI) | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.2 (robust | 50 | 0.30 (0.15) | 31% frail 41% prefrail 26% robust | Referenced a study by a co-author, Cohen et al. [22] |
Cohen 2016 USA [22] Observational | Various | 500 | 73 (6.18) | Deficit-Accumulation Frailty Index (DAFI) | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.2 (robust/nonfrail) | 51 | NR | 11% frail 39% prefrail 50% nonfrail | Referenced a study by co-authors, Sheppard et al. [34] |
Mandelblatt 2021 USA [31] Observational | Breast | 708b including 355 non-cancer controls | 68.2 (6.0) cancer 67.9 (7.1) control | Deficits Accumulation Score | > 0.35 (frail) 0.20 ≤ FI < 0.35 (prefrail) < 0.20 (robust) | 42 | 0.15 (0.08) | NR | |
Bluethmann 2017 USA [21] Observational | Breast | 990b | 72.6 (5.9) | Frailty Index | > 0.35 (frail) 0.2 < FI ≤ 0.35 (pre-frail) 0–0.2 (robust) | 35 | NR | 22.9% pre-frail/frail 77.1% robust | Referenced study by co-authors Sheppard et al. [34] |
Mandelblatt 2017 USA [29] Observational | Breast | 1280b | 72.4 (5.9) | Frailty Index | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.20 (robust) | 35 | NR | 5.1% frail 18.3% pre-frail 76.7% robust | Referenced a study by co-authors, Cohen et al. [22] |
Negrete-Najar 2021 USA [68] Observational | Pancreatic | 440 | Median 76 (range 70–91) | Frailty Index | ≥ 0.35 (frail) 0.20 ≤ FI < 0.35 (pre-frail) < 0.20 (fit) | 61 | 0.26 (0.09) | 16.6% frail 58% prefrail 25.5% fit | |
Weiss 2020 USA [36] Non-randomised experimental study | Lung | 42 | 76.3 (range 71–84) | Frailty Index | > 0.35 (frail) 0.2 ≤ FI ≤ 0.35 (prefrail) < 0.2 (robust) | 35 | NR | 42% frail 39% prefrail 19% robust | Nil |
Wang 2019 China [35] Observational | Lung | 1020d | Median 65 (NR) | Frailty Index Based on Laboratory Variables (FI-LAB) | ≥ 0.35 (frail) 0.20—0.35 (pre-frail) 0—0.2 (robust) | 44 | median 0.14 (range 0—0.61) | 4.9% frail 26.4% pre-frail | Referenced Cohen et al. [22] |
Sheppard 2014 USA [34] Observational | Breast | 1288b | 72.78 (6.05) | Frailty Score | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.2 (robust) | 35 | NR | 4.9% frail 18.7% prefrail 76.4% robust | |
Mandelblatt 2016 USA [28] Observational | Breast | 1280b | 72.7 (5.9) | Searle Index | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.2 (robust) | 35 | NR | 5.1% frail 18.3% pre-frail 76.7% robust | Referenced co-authored study by Sheppard et al. [34] Also referenced Rockwood et al., which did not report this FI categorisation. [64] |
Mandelblatt 2018 USA [30] Observational | Breast | 691b including 347 non-cancer control | 67.8 (7.0) cancer 68.1 (6.1) control | Searle's Deficits Accumulation Index | ≥ 0.35 (frail) 0.2 ≤ FI < 0.35 (prefrail) < 0.20 (robust) | 40 | NR | 25.6% prefrail/frail 74.4% robust | Referenced Rockwood et al., [64] which did not report this FI categorisation |
Martinez-Tapia 2022 France [40] Observational | Various | 1136 | Median 80 (IQR 76–85) | Geriatric Assessment Frailty Index | ≥ 0.30 (unfit) < 0.30 (fit) | 52 | NR | 88.8% unfit 11.2% fit | Referenced Searle et al. [27] which did not categorise FI. Author comments that an FI > 0.20 would have categorised 99% as unfit and limited analysis |
Inci 2021 Germany [59] Observational | Ovarian | 144 | Median 58 (range 18–87) | Frailty Index | > 0.26 (frail) ≤ 0.26 (non-frail) | 30 | NR | 33% frail 67% non-frail | Authors used receiver operator characteristic analyses and logistic regression to determine that an FI > 0.26 showed the best predictive threshold for severe complications (> IIIB according to Clavien Dindo) For overall survival the Log Rank test showed the best cut-off with FI > 0.15 |
Giannotti 2022 Italy [43] Non-randomised experimental study | Gastrointestinal | 208 | Median 80 (IQR 77.4–84.0) | 40-Item Frailty Index (40-FI) | ≥ 0.25 (frail) 0.8 < FI < 0.25 (prefrail) ≤ 0.08 (fit) | 40 | Median 0.15 (IQR 0.10—0.26) | NR | Referenced an abstract which did not categorise frailty [69]. |
McCarthy 2018 Australia [44] Observational | Solid tumour | 175 | 72 (5.2) | FI-CGA | > 0.25 (frail) ≤ 0.25 (fit) | 42 | 0.31 (0.14); 0.27 (0.21—0.39) | 53.7% frail 46.3% fit | Referenced a review article by Rockwood et al. [70] Demonstrated construct validity against fitness and vulnerability as measured by the VES-13, and by doctor assessment |
Reiser 2021 Austria [46] Observational | Gynaecological | 83 | 84.2 (3.5) | Frailty Index | ≥ 0.25 (frail) < 0.25 (non-frail) | 31 | 0.19 (0.16) | 24.1% frail 75.9% non-frail | |
Giannotti 2019 Italy [42] Non-randomised experimental study | Gastrointestinal | 99 | 80.18 (5.88) | Frailty Index (FI) | ≥ 0.25 (frail) 0.8 < FI < 0.25 (prefrail) ≤ 0.08 (fit) | 40 | 0.22 (0.13) | 40.5% frail 50.5% prefrail 9% fit | Referenced Rockwood et al.’s study, [71] which demonstrated construct and predictive validity of CFS categories. FI 0.25 represented the crossing point between CFS 4 (‘apparently vulnerable’, mean FI 0.22), and CFS 5 (‘mildly frail’, mean FI 0.27) Authors conducted pair-wise analyses of ROC curves for CGA and FI that showed similar accuracy in identifying 1-year mortality and functional outcomes. An FI cut-off of 0.19 showed the best predictive threshold for 1-year mortality, and between 0.15 and 0.18 for 1-year functional status |
Pérez-Zepeda 2016 Mexico [45] Observational | Various including non-cancer population | 8 022: 288 with cancer | 70.6 (7.4) | Frailty Index (FI) | ≥ 0.25 (frail) | 55 | 0.196 (0.108) | 29.9% frail | Referenced Rockwood et al. [10] |
Geessink 2017 Netherlands [41] Observational | Various including non-cancer population | 7 493: 751 with cancer | 79.1 (6.5) | TOPICS-FI38 | > 0.25 (frail) | 38 | 0.23 (0.13) | NR | Nil |
Zhang 2022 USA [47] Observational | Various | 2 050 cancer survivors including 9 474 controls | Cancer survivors, 72.6 (7.1) | Frailty Index (FI) | > 0.21 (frailty) 0.10 < FI ≤ 0.21 (prefrailty) ≤ 0.10 (fitness) | 45 | NR | 55.9% frail 38.2% prefrail 5.9% fit | |
Bensken 2022 USA [48] Observational | Breast Colorectal Prostate Lung | 29 140 | NR | Claims Frailty Index (CFI) | ≥ 0.4 (severely frail) 0.3 < FI < 0.4 (moderately frail) 0.20 < FI < 0.30 (mildly frail) 0.10 < FI < 0.20 (pre-frail) < 0.10 (non-frail) | 93 | Breast 0.15 (0.06) Colorectal 0.16 (0.06) Lung 0.16 (0.07) Prostate 0.13 (0.05) | 3.5% severely / moderately frail 14.2% mildly frail 75.4% pre-frail 7% non-frail | Referenced CFI validation study by a co-author, [76] which did not categorise the CFI, but did demonstrate that 0.1 increments predicted increased risk of mortality, functional decline, mobility impairment and recurrent falls |
Cooper 2022 USA [50] Observational | Lung | 73 | Median 76.7 (IQR 72.3 – 80.5) | Comprehensive Geriatric Assessment-Based Frailty Index (FI-CGA) | > 0.2 (frail) > 0.4 (severe frailty) 0.2 < FI ≤ 0.4 (occult frailty) ≤ 0.2 (non-frail) | 45 | NR | 38.3% frail 6.8% severe frailty 31.5% occult frailty 61.6% non-frail | Referenced Rockwood et al. [77] ‘Occult frailty’ was referred to as a level of frailty often missed by surgical teams without the use of CGA |
Shen 2021 China [52] Observational | Lung | 997d | 66.07 (4.90) | Electronic Frailty Index (EFI) | ≥ 0.20 (frail) < 0.20 (non-frail/robust) | 35 | NR | 19.7% frail 80.3% non-frail/robust | |
Tariciotti 2022 Italy [53] Observational | Meningioma | 165 | Median 63 (IQR 52–72) | Frailty Index (FI) | > 0.20 (frail) 0.10—0.20 (semi-fit) < 0.10 (fit) | 34 | Median 0.16 (IQR 0.06–0.18) | 11.5% frail 46.7% semi-fit 41.8% fit | |
Hembree 2021 USA [51] Observational | Various | 189 | Median 62.0 (range 26–87) | Frailty Index (FI) And Test Based Frailty Index (TBFI) | > 0.4 (severely frail) 0.3—0.4 (moderately frail) 0.2—0.3 (mildly frail) 0—0.2 (non-frail) | 53 | 0.28 (0.12) | 20.1% severely frail 30.7% moderately frail 32.8% mildly frail 10.5% non-frail | Referenced Jayanama et al. [80] |
Cheng 2022 USA [49] Observational | Non-small cell lung cancer | 42 204 | 74.1 (6.3) | Veterans Affairs Frailty Index (VAFI) | > 0.3 (moderate-to-severely frail) 0.2—0.3 (mildly frail) 0.1—0.2 (pre-frail) 0—0.1 (non-frail) | 31 | 0.25 (0.13) | 27.8% moderate-severely frail 27.8% mildly frail 31.6% pre-frail 12.9% non-frail | |
Narasimhulu 2020 USA [55] Observational | Ovarian | 169e | Frail: 67.9 (9.4) Non-frail: 62.3 (10.7) | Frailty Deficit Index | ≥ 0.15 (frail) < 0.15 (non-frail) | 30 | NR | 17.2% frail 82.7% non-frail | |
Kumar 2017 USA [54] Observational | Ovarian | 535e | 64.3 (11.3) | Frailty Deficit Index (FI) | ≥ 0.15 (frail) < 0.15 (non-frail) | 30 | median 0.08 (IQR 0.03—0.14) | 24.% frail 75.5% non-frail | Authors derived the cut-off that yielded the highest Youden's index for their three binary outcomes (Accordion Grade 3 or 4 complication, 90-day mortality, receipt of chemotherapy within 42 days), while yielding the highest separation in outcome rates between frail and non-frail |
Yao 2019 USA [56] Observational | Ovarian | 535e | 64.3 (11.3) | Frailty Index | ≥ 0.15 (frail) < 0.15 (non-frail) | 30 | NR | 24.5% frail 75.7% non-frail | Same group and study population as Kumar et al. [54] |
Jauhari 2020 UK [57] Observational | Breast | 67 925 External validation 4230 | NA | Secondary Care Administrative Records Frailty (SCARF) Index | ≥ 0.19 (severe frailty) 0.12—0.18 (moderate frailty) 0.06—0.11 (mild frailty) ≤ 0.05 (fit) | 36 | 0.05 (NR) | 3.3% severe frailty 6.6% moderate frailty 11% mild frailty 79.2% fit | No reference for categories Authors tested internal validation, and then external validation in a separate cohort of 4230 women |