| Literature DB >> 35486640 |
Admassu N Lamu1,2, Lars Björkman3,4, Harald J Hamre5, Terje Alræk6, Frauke Musial6, Bjarne Robberstad2.
Abstract
There are many patients in general practice with health complaints that cannot be medically explained. Some of these patients attribute their health complaints to dental amalgam restorations. This study examined the cost-effectiveness of the removal of amalgam restorations in patients with medically unexplained physical symptoms (MUPS) attributed to amalgam fillings compared to usual care, based on a prospective cohort study in Norway. Costs were determined using a micro-costing approach at the individual level. Health outcomes were documented at baseline and approximately two years later for both the intervention and the usual care using EQ-5D-5L. Quality adjusted life year (QALY) was used as a main outcome measure. A decision analytical model was developed to estimate the incremental cost-effectiveness of the intervention. Both probabilistic and one-way sensitivity analyses were conducted to assess the impact of uncertainty in costs and effectiveness. In patients who attribute health complaints to dental amalgam restorations and fulfil the inclusion and exclusion criteria, amalgam removal is associated with modest increase in costs at societal level as well as improved health outcomes. In the base-case analysis, the mean incremental cost per patient in the amalgam group was NOK 19 416 compared to the MUPS group, while mean incremental QALY was 0.119 with a time horizon of two years. Thus, the incremental costs per QALY of the intervention was NOK 162 680, which is usually considered cost effective in Norway. The estimated incremental cost per QALY decreased with increasing time horizon, and amalgam removal was found to be cost saving over both 5 and 10 years. This study provides insight into the costs and health outcomes associated with the removal of amalgam restorations in patients who attribute health complaints to dental amalgam fillings, which are appropriate instruments to inform health care priorities.Entities:
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Year: 2022 PMID: 35486640 PMCID: PMC9053791 DOI: 10.1371/journal.pone.0267236
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Baseline characteristics.
| Variable (n, %) | Amalgam (n = 32) | MUPS (n = 28) | ||
|---|---|---|---|---|
| Age (Mean, SD) | 52 | 7.5 | 50 | 10.3 |
| Gender | ||||
| Female | 19 | 59.4 | 24 | 85.7 |
| Male | 13 | 40.6 | 4 | 14.3 |
| Education | ||||
| Lower and upper secondary | 14 | 43.8 | 17 | 60.7 |
| College, <4yrs | 11 | 34.4 | 9 | 32.1 |
| College, 4+ years | 7 | 21.9 | 2 | 7.1 |
| Live without partner (Yes/No) | ||||
| Yes | 26 | 81.3 | 23 | 82.1 |
| No | 16 | 18.7 | 5 | 17.9 |
| Income (in ‘000) | ||||
| Low, < 450 | 8 | 25.8 | 4 | 14.3 |
| Middle, 450–750 | 13 | 41.9 | 13 | 46.4 |
| High, 750+ | 10 | 32.3 | 11 | 39.3 |
| Smoking status | ||||
| Current smokers | 5 | 15.6 | 7 | 22.2 |
| Non-smokers | 27 | 84.4 | 21 | 77.8 |
| Alcohol intake | ||||
| Never | 4 | 12.5 | 6 | 21.4 |
| Sometimes | 21 | 65.6 | 16 | 57.1 |
| Frequently | 7 | 21.9 | 6 | 21.4 |
| Concentration of inorganic mercury in serum* | ||||
| ≥ 0.2 μg/L | 16 | 50.0 | 13 | 48.1 |
| < 0.2 μg/L | 16 | 50.0 | 14 | 51.9 |
SD: Standard deviation; MUPS: Medically unexplained physical symptoms. * Data available for n = 27 in the MUPS cohort.
Fig 1Decision model tree structure showing comparison of amalgam fillings removal (AR), and usual care (UC).
The squares denote decision nodes, circles denote probability nodes, and triangles denote the terminal nodes.
Utility and probability parameters in different health states.
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| Deterioration (reduction >0.037) | 9.4 | 46.4 | 0.599 (0.137) |
| The same (difference of ± ≤0.037) | 21.9 | 14.3 | |
| Improvement (increase >0.037) | 68.7 | 39.3 | |
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| Baseline | 0.609 (0.216) | 0.696 (0.170) | |
| Follow-up | 0.698 (0.165) | ||
| Mean change | 0.002 (0.146) | ||
AR: Amalgam removal; MUPS: Medically unexplained physical symptoms; UC: Usual care; SD: Standard deviation; EQ-5D: EuroQol 5-dimension.
a Utility values for the described health states are similar for both the intervention and the MUPS.
* p < 0.001. The data in panel A were used as model input, while the data in panel B validates the implication that amalgam removal has the potential to improve HRQoL.
Costs and utility parameters with different time horizons.
| Input parameters | 95% CI | ||||
|---|---|---|---|---|---|
| Mean | SE | Low | High | Distribution | |
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| Treatment: AR | 17 630 | 2 385 | 12 766 | 22 493 | Gamma |
| Intervention: AR | 80 400 | 16 047 | 44 397 | 92 823 | Gamma |
| Usual care: UC | 78 614 | 11 592 | 52 780 | 119 459 | Gamma |
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| Deterioration | 1.152 | 0.062 | 1.028 | 1.277 | Normal |
| Same | 1.42 | 0.110 | 1.221 | 1.618 | Normal |
| Improvement | 1.486 | 0.047 | 1.392 | 1.581 | Normal |
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| Intervention: AR | 157 052 | 26 923 | 99 286 | 191 236 | Gamma |
| Usual care: UC | 206 385 | 41 431 | 120 844 | 306 937 | Gamma |
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| Deterioration | 2.720 | 0.147 | 2.426 | 3.014 | Normal |
| Same | 3.352 | 0.236 | 2.883 | 3.819 | Normal |
| Improvement | 3.508 | 0.111 | 3.285 | 3.732 | Normal |
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| Intervention: AR | 266 366 | 42 434 | 177 564 | 331 588 | Gamma |
| Usual care: UC | 388 603 | 83 986 | 217 912 | 574 305 | Gamma |
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| Deterioration | 4.956 | 0.268 | 4.052 | 5.034 | Normal |
| Same | 6.108 | 0.430 | 4.814 | 6.378 | Normal |
| Improvement | 6.391 | 0.203 | 5.487 | 6.233 | Normal |
CI: Confidence interval; AR: Amalgam removal; UC: Usual care; SE: Usual error; NOK: Norwegian kroner; QALYs: Quality Adjusted Life Years.
Cost-effectiveness of amalgam removal in the base-case and various scenario analyses.
| UC: MUPS | Intervention: AR | Incremental | |||||
|---|---|---|---|---|---|---|---|
| Cost | QALY | Cost | QALY | ΔCost | ΔQALY | ICER | |
| At 2 years follow-up (base-case) | 78 614 | 1.321 | 98 030 | 1.44 | 19 416 | 0.119 | 162 680 |
| At 5 years follow-up | 206 385 | 3.118 | 174 682 | 3.4 | -31 703 | 0.282 | Dominance¤ |
| At 10 years follow-up | 388 603 | 5.682 | 283 996 | 6.195 | -104 607 | 0.513 | Dominance |
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| At 2 years follow-up (base-case) | 78 614 | 1.106 | 98 030 | 1.243 | 19 416 | 0.138 | 141 198 |
| At 5 years follow-up | 206 385 | 2.61 | 174 682 | 2.935 | -31 703 | 0.324 | Dominance |
| At 10 years follow-up | 388 603 | 4.756 | 283 996 | 5.347 | -104 607 | 0.592 | Dominance |
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| At 2 years follow-up (base-case) | 78 614 | 1.401 | 98 030 | 1.528 | 19 416 | 0.126 | 153 493 |
| At 5 years follow-up | 206 385 | 3.503 | 174 682 | 3.819 | -31 703 | 0.316 | Dominance |
| At 10 years follow-up | 388 603 | 7.005 | 283 996 | 7.638 | -104 607 | 0.632 | Dominance |
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| At 2 years follow-up (base-case) | 78 614 | 1.284 | 98 030 | 1.401 | 19 416 | 0.116 | 167 161 |
| At 5 years follow-up | 206 385 | 2.951 | 174 682 | 3.217 | -31 703 | 0.266 | Dominance |
| At 10 years follow-up | 388 603 | 5.156 | 283 996 | 5.621 | -104 607 | 0.466 | Dominance |
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| At 2 years follow-up (base-case) | 106 657 | 1.321 | 114 185 | 1.44 | 7 528 | 0.119 | 63 075 |
| At 5 years follow-up | 335 568 | 3.118 | 196 596 | 3.4 | -138 972 | 0.282 | Dominance |
| At 10 years follow-up | 662 027 | 5.682 | 314 125 | 6.195 | -347 902 | 0.513 | Dominance |
QALY: Quality-adjusted life year; ICER: Incremental cost-effectiveness ratio; UC: Usual Care. ¤ Dominance appears because Amalgam removal is less costly than MUPS, while at the same time being more effective. With dominance, Amalgam removal is cost-effective irrespective of willingness to pay for health.
Fig 2Tornado diagram illustrating results from one-way sensitivity analyses.
UC: Usual care; AR: Amalgam removal; ICER: Incremental cost-effectiveness ratio.
Fig 3Results from Monte Carlo simulation with 10 000 iterations.
Panel a) illustrates the cost-effectiveness pairs for ‘Amalgam removal’ compared to ‘Usual care’, and panel b) shows the cost-effectiveness acceptability curves that illustrate the probabilities that either intervention alternative is cost-effective for a range of cost-effectiveness thresholds. Dashed (orange) line is the minimum cost-effectiveness threshold of 275 000 NOK.